Blood pressure health management method and platform

Abstract

The invention provides a blood pressure health management method and platform, and relates to the field of blood pressure health management. The blood pressure health management method is applied to a plurality of target users associated with at least one blood pressure monitoring device. The blood pressure health management method comprises the steps of obtaining at least one piece of blood pressure data of a target user in a target user database; wherein the blood pressure data comprises blood pressure data monitored by blood pressure monitoring equipment; managing the target user at least based on the at least one piece of blood pressure data, and generating a blood pressure health management suggestion of the target user; wherein the blood pressure health management suggestions comprise ablation operation suggestions. According to the blood pressure health management method and platform, multiple users are managed by acquiring the blood pressure data of the target user, and personalized health management suggestions including ablation operation suggestions are generated, so that the accuracy and effectiveness of blood pressure health management are improved.

Description

Technical Field

[0001] This application relates to the field of blood pressure health management, and more particularly, to a blood pressure health management method and platform. Background Art

[0002] In recent years, with the changes in lifestyle and the aging of the population, the incidence of hypertension has increased significantly, and the problem of abnormal blood pressure has become increasingly prominent. Therefore, some blood pressure management platforms have emerged, aiming to systematically monitor and manage the health status of users; through real-time data tracking and analysis, help users master their blood pressure changes and other health parameters, so as to promote more effective self-management and early intervention, and improve the overall health level.

[0003] Existing blood pressure management systems or platforms are mainly divided into two categories: one is a blood pressure monitoring and management tool for ordinary users, and the other focuses on the health management of hypertensive patients. However, these two types of systems are often independent and cannot comprehensively manage the health needs of different types of users.

[0004] Currently, there is a lack of a unified management platform that can take into account both ordinary users and hypertensive patients, unable to manage ordinary users and hypertensive patients in a personalized manner, unable to give suggestions on whether to perform hypertensive treatment surgery according to the conditions of different patients, and give surgical suggestions and plans before, during, and after the operation, resulting in insufficient personalized guidance and support. Summary of the Invention

[0005] The purpose of the embodiments of this application is to provide a blood pressure health management method and platform. The blood pressure health management method can manage ordinary users and patient users, manage target users based on at least one piece of blood pressure data of a patient, and give targeted suggestions to the target users; it can not only expand the scope of patient screening applicable to RDN surgery, but also detect patients in the early stage of hypertension, help them effectively control the development of the disease, so as to help control blood pressure and improve the health status.

[0006] In a first aspect, the embodiments of this application provide a blood pressure health management method, which is applied to multiple target users associated with at least one blood pressure monitoring device; the blood pressure health management method includes: obtaining at least one piece of blood pressure data of a target user from a target user database; wherein, the blood pressure data includes the blood pressure data monitored by a blood pressure monitoring device; managing the target user based on at least one piece of blood pressure data, and generating a blood pressure health management suggestion for the target user; wherein, the blood pressure health management suggestion includes an ablation surgery suggestion.

[0007] In the above implementation process, the blood pressure health management method provided by the embodiments of the present application can manage both ordinary users and patient users, manage target users based on at least one piece of blood pressure data of patients, and give targeted suggestions to the target users; it can not only expand the scope of patient screening applicable to RDN surgery, but also detect patients in the early stage of hypertension, help them effectively control the development of the disease, thereby helping to control blood pressure and improve health conditions.

[0008] Optionally, in the embodiments of the present application, the blood pressure monitoring device includes a self - blood pressure monitoring device; the blood pressure data includes the user - end blood pressure data corresponding to the self - blood pressure monitoring device; the target user includes an ordinary user; at least based on at least one piece of blood pressure data, manage the target user and generate a blood pressure health management suggestion for the target user, including: manage the ordinary user according to at least one piece of user - end blood pressure data and generate an actionable blood pressure health management suggestion for the ordinary user.

[0009] Optionally, in the embodiments of the present application, manage the ordinary user according to at least one piece of user - end blood pressure data and generate an actionable blood pressure health management suggestion for the ordinary user, including: determine the blood pressure reference level of the ordinary user based on at least one piece of user - end blood pressure data; wherein the blood pressure reference level includes an ideal blood pressure level, a borderline hypertension blood pressure level, and a hypertension warning blood pressure level; if it is determined that the blood pressure reference level of the ordinary user is the ideal blood pressure level, push hypertension publicity information to the ordinary user; if it is determined that the blood pressure reference level of the ordinary user is the borderline hypertension blood pressure level, push lifestyle intervention suggestions for blood pressure reduction and medical advice to the ordinary user; if it is determined that the blood pressure reference level of the ordinary user is the hypertension warning blood pressure level, push a medical warning message to the target user.

[0010] In the above implementation process, the blood pressure health management method provided by the embodiments of the present application can effectively manage the blood pressure health of users by systematically analyzing the blood pressure data of ordinary users. First, by determining the blood pressure reference level of the user, the health status of the user is identified, and then personalized suggestions are provided. For example, for users with normal blood pressure, the system pushes hypertension publicity information to consolidate healthy habits; for users with borderline blood pressure, lifestyle intervention suggestions for blood pressure reduction and medical advice are provided; and for users with warning - level blood pressure, a medical warning message is pushed in a timely manner to ensure that they can quickly obtain professional medical help. The dynamic management and targeted suggestions for ordinary users not only enhance the health awareness of users, but also promote early intervention, ultimately helping to improve the overall health condition and reduce the risks related to hypertension.

[0011] Optionally, in the embodiments of the present application, the target users further include patient users; the blood pressure data further includes hypertension diagnosis information; managing ordinary users based on at least one piece of user-side blood pressure data further includes: determining an ordinary user as a patient user according to the user-side blood pressure data and the hypertension diagnosis information.

[0012] In the above implementation process, the blood pressure health management method provided by the embodiments of the present application can effectively identify users who have been diagnosed with hypertension by analyzing the users' blood pressure data and diagnosis information, and convert the user from an ordinary user to a patient user, so as to provide personalized management suggestions and intervention measures for them. It ensures a clear boundary between ordinary users and patient users, enabling patients to obtain targeted lifestyle adjustment, medication management, and regular examination suggestions, effectively controlling the development of the condition, and improving the overall health status. On the other hand, this dynamic management mechanism not only enhances users' health awareness but also provides more detailed data support for medical staff, helping them make more scientific treatment decisions, and ultimately improving the overall effect of hypertension management.

[0013] Optionally, in the embodiments of the present application, managing target users based on at least one piece of blood pressure data and generating blood pressure health management suggestions for the target users further includes: pushing medical intervention suggestions to patient users according to the blood pressure data.

[0014] In the above implementation process, the blood pressure health management method provided by the embodiments of the present application can not only provide real-time and professional guidance for patient users but also improve patients' awareness and management ability of their own conditions. Timely medical intervention suggestions can promote patients to comply with medical advice, improve the treatment effect, and reduce the risk of complications caused by out-of-control blood pressure.

[0015] Optionally, in the embodiments of the present application, pushing medical intervention suggestions to patient users according to the blood pressure data includes: determining the clinical blood pressure level of the patient user according to the user-side blood pressure data and the hypertension diagnosis information; wherein, the clinical blood pressure level includes the moderate-severe hypertension level; if it is determined that the clinical blood pressure level of the patient user is the moderate-severe hypertension level, then push medication warning information to the patient user.

[0016] Optionally, in the embodiments of the present application, the blood pressure data further includes cardiovascular diagnosis information; the clinical blood pressure levels further include the normal high-value blood pressure level and the mild hypertension level; according to the blood pressure data, pushing medical intervention suggestions to the patient user further includes: if it is determined that the clinical blood pressure level of the patient user is the normal high-value blood pressure level or the mild hypertension level, generating a blood pressure health management suggestion for the patient user according to the cardiovascular diagnosis information of the patient user; in the case where the clinical blood pressure level of the patient user is the normal high-value blood pressure level and the cardiovascular diagnosis information is low-risk or medium-risk; or, in the case where the clinical blood pressure level of the patient user is the mild hypertension level and the cardiovascular diagnosis information is low-risk, generating a blood pressure-lowering lifestyle intervention suggestion; in the case where the cardiovascular diagnosis information of the patient user is the normal high-value blood pressure level and the cardiovascular diagnosis information is high-risk or very high-risk, generating a medication suggestion; in the case where the cardiovascular diagnosis information of the patient user is the mild hypertension level and the cardiovascular diagnosis information is medium-risk or high-risk or very high-risk, generating a medication warning information.

[0017] In the above implementation process, when the blood pressure of the patient is at the normal high value or mild hypertension level, the blood pressure health management method provided by the embodiments of the present application provides corresponding lifestyle intervention or drug treatment suggestions in combination with the cardiovascular conditions, ensuring timely health management. It can be seen that the blood pressure health management method provided by the embodiments of the present application is a dynamic management method based on risk assessment, which not only improves the patient's sense of participation in health management, but also effectively prevents the occurrence of cardiovascular events and optimizes the overall treatment effect.

[0018] Optionally, in the embodiments of the present application, the blood pressure health management method further includes: after generating the medication warning information or the medication suggestion, judging whether the patient user is a patient with poor drug control according to the blood pressure data of the patient user corresponding to the generated medication warning information or the medication suggestion within a preset time period; and, in the case of generating the medication warning information or the medication suggestion, judging whether the corresponding patient user is a patient who cannot use drugs; if the patient user is a patient with poor drug control or a patient who cannot use drugs, generating an ablation surgery suggestion; after confirming that the patient user will undergo an ablation surgery through a preoperative planning plan, determining the patient user as a surgical user and generating a surgical planning suggestion for the surgical user.

[0019] In the above implementation process, when a patient is determined to have poor drug control or be unable to use drugs, the blood pressure health management method according to the embodiments of the present application promptly generates ablation surgery suggestions to ensure that the patient can still obtain effective hypertension management when the drug treatment effect is not ideal. At the same time, the implementation of the preoperative planning scheme not only fully communicates with the patient to clarify the benefits and risks of the surgery, but also ensures that the patient's indications and contraindications are accurately identified through the confirmation of the medical staff, thereby optimizing the treatment plan and improving the patient's safety and treatment effect. The comprehensive management strategy provided by the embodiments of the present application helps to improve the overall health status of the patient and reduce the risk of cardiovascular events.

[0020] Optionally, in the embodiments of the present application, the generation of the surgery planning suggestions for the surgery user includes: identifying the tissue morphology and tissue size of the target tissue of the surgery user according to the preoperative image data; determining the standard blood pressure level of the surgery user according to the preoperative quantitative data; and determining the planned ablation position, planned ablation points, planned ablation time, and planned surgery duration of the surgery user according to the tissue morphology, tissue size, standard blood pressure level, basic patient information of the surgery user, and historical ablation surgery planning scheme.

[0021] Optionally, in the embodiments of the present application, a patient information report is generated according to the basic patient information of the surgery user, including: obtaining the basic patient information of the surgery user; where the basic patient information includes height, weight, genetic history, and / or allergy history; performing data preprocessing on the basic patient information; extracting the patient information characteristics of the preprocessed basic patient information, and obtaining the patient information report based on the target neural network model.

[0022] Optionally, in the embodiments of the present application, determining the standard blood pressure level of the surgery user according to the preoperative quantitative data includes: obtaining the preoperative quantitative data; where the preoperative quantitative data includes blood pressure, heart rate, and / or blood sugar for 24 hours; performing data preprocessing on the preoperative quantitative data; extracting the level characteristics of the preprocessed preoperative quantitative data, and training and evaluating based on a preset machine model to generate the standard blood pressure level.

[0023] In the above implementation process, the blood pressure health management method provided by the embodiments of the present application realizes personalized and precise surgery planning by integrating a variety of patient data and intelligent models. The surgery planning suggestions generated using preoperative images and patient quantitative data reduce the surgical risk while ensuring the ablation surgery effect. The intelligent surgery planning model further automates the data processing process and planning generation, improves the accuracy and reliability of the operation, provides scientific support for medical staff, and helps with efficient and personalized blood pressure health management and surgery implementation.

[0024] Optionally, in the embodiments of the present application, the blood pressure health management method further includes: monitoring at least one blood pressure data of the surgical user after ablation surgery, and pushing postoperative recovery suggestions to the patient user.

[0025] In the above implementation process, after ablation surgery, the blood pressure changes of the patient are regularly recorded and analyzed to evaluate the effect of the surgery and the overall health status of the patient. By using a remote monitoring device, the blood pressure information of the patient can be obtained in a timely manner to ensure that it is within the normal range and potential complications can be detected.

[0026] In a second aspect, the embodiments of the present application provide a blood pressure health management system, which is characterized in that the blood pressure health management system includes a device management module, a user management module, and a user database; the device management module is configured to bind a blood pressure monitoring device associated with a target user, obtain the blood pressure data measured by the blood pressure monitoring device, and store it in the user database; the user management module is configured to manage the target user according to at least one blood pressure data of the target user and push blood pressure health management suggestions to the user terminal.

[0027] In the above implementation process, the blood pressure health management system provided by the embodiments of the present application makes full use of the combination of the device management module and the user management module to realize real-time monitoring and intelligent analysis of the user's blood pressure. Through automated data collection and personalized health management suggestions, the system not only improves the user's health awareness and participation, but also effectively promotes the long-term effect of blood pressure control, and finally realizes the goal of optimizing the patient's health management.

[0028] Optionally, in the embodiments of the present application, the blood pressure monitoring device includes an autonomous blood pressure monitoring device, the blood pressure data includes the user terminal blood pressure data corresponding to the autonomous blood pressure monitoring device, and the target user includes an ordinary user; the user management module includes an ordinary user management unit, and the ordinary user management unit is configured to: determine the blood pressure reference level of the ordinary user according to at least one user terminal blood pressure data and store the blood pressure reference level in the user database; wherein, the blood pressure reference level includes an ideal blood pressure level, a borderline hypertension blood pressure level, and a hypertension warning blood pressure level; if it is determined that the blood pressure reference level of the ordinary user is the ideal blood pressure level, hypertension publicity information is pushed to the user terminal; if it is determined that the blood pressure reference level of the ordinary user is the borderline hypertension blood pressure level, lifestyle intervention suggestions for reducing blood pressure and medical advice are pushed to the user terminal; if it is determined that the blood pressure reference level of the ordinary user is the hypertension warning blood pressure level, medical warning information is pushed to the user terminal.

[0029] Optionally, in the embodiments of the present application, the target users further include patient users; the user management module further includes a patient user management unit; the user management module is further configured to obtain blood pressure data including the hypertension diagnosis information of the target users at the medical staff side, and in the case where the target user is an ordinary user, convert the ordinary user into a patient user and store the hypertension diagnosis information in the user database; the patient user management unit is configured to determine the clinical blood pressure level of the patient user according to the user-side blood pressure data and the hypertension diagnosis information; wherein the clinical blood pressure level includes normal high-value blood pressure, mild hypertension level, and moderate-severe hypertension level; and if it is determined that the clinical blood pressure level of the patient user is the moderate-severe hypertension level, a medication warning message is pushed to the user side.

[0030] Optionally, in the embodiments of the present application, the user management module is further configured to obtain the cardiovascular diagnosis information of the patient user at the medical staff side and store the cardiovascular diagnosis information in the user database; the patient management unit is further configured to, in the case where the clinical blood pressure level of the patient user is the normal high-value blood pressure level and the cardiovascular diagnosis information is low-risk or medium-risk; or, in the case where the clinical blood pressure level of the patient user is the mild hypertension level and the cardiovascular diagnosis information is low-risk, push a blood pressure-lowering lifestyle intervention suggestion to the user side; in the case where the cardiovascular diagnosis information of the patient user is the normal high-value blood pressure level and the cardiovascular diagnosis information is high-risk or very high-risk, push a medication suggestion to the user side; in the case where the cardiovascular diagnosis information of the patient user is the mild hypertension level and the cardiovascular diagnosis information is medium-risk or high-risk or very high-risk, push a medication warning message to the user side.

[0031] Optionally, in the embodiments of the present application, the user management module further includes a surgical user management unit; the surgical user management unit is configured to manage patient users who are patients with poor drug control or who are unable to use drugs.

[0032] Optionally, in the embodiments of the present application, the surgical user management unit is further configured to: identify the tissue morphology and tissue size of the target tissue of the surgical user according to the preoperative image data; determine the standard blood pressure level of the surgical user according to the preoperative quantitative data; push a surgical planning suggestion including the planned ablation position, planned ablation points, planned ablation time, and planned surgical duration of the surgical user to the user side and the medical staff side according to the tissue morphology, tissue size, standard blood pressure level, basic patient information of the surgical user, and the historical ablation surgery planning scheme; and monitor at least one blood pressure data of the surgical user after the ablation surgery is performed and push a postoperative recovery suggestion to the patient user.

[0033] Optionally, in the embodiments of the present application, the blood pressure health management system shares at least part of the target user data with a third-party platform.

[0034] In a third aspect, an embodiment of the present application provides a health management device, including: a processor and a memory. Among them, computer program instructions suitable for execution by the processor are stored in the memory. When the computer program instructions are run by the processor, the processor is caused to execute the following methods: obtaining at least one blood pressure data of a target user from a target user database; wherein the blood pressure data includes blood pressure data monitored by at least one blood pressure monitoring device associated with the target user; managing the target user based on at least one blood pressure data and generating a blood pressure health management recommendation for the target user.

[0035] In a fourth aspect, an embodiment of the present application provides an electronic device, which includes a memory and a processor. When the processor reads and runs program instructions stored in the memory, it executes the steps in any implementation manner of the above blood pressure health management method.

[0036] In a fifth aspect, an embodiment of the present application further provides a computer-readable storage medium, in which computer program instructions are stored. When the computer program instructions are read and run by a processor, the steps in any implementation manner of the above blood pressure health management method are executed. Description of the Drawings

[0037] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings required to be used in the embodiments of the present application. It should be understood that the following drawings only show some embodiments of the present application, and therefore should not be regarded as a limitation of the scope. For those of ordinary skill in the art, without creative efforts, other related drawings can also be obtained based on these drawings.

[0038] Figure 1 It is a flowchart of the blood pressure health management method provided by the embodiment of the present application;

[0039] Figure 2 It is a flowchart of general user management provided by the embodiment of the present application;

[0040] Figure 3 It is a schematic diagram of a general user being converted into a patient user provided by the embodiment of the present application;

[0041] Figure 4 It is a flowchart of patient user management provided by the embodiment of the present application;

[0042] Figure 5 It is a flowchart of surgical planning recommendation generation provided by the embodiment of the present application;

[0043] Figure 6 It is a block diagram of surgical planning model training provided by the embodiment of the present application;

[0044] Figure 7 Schematic diagram of using the UNet3D network model for renal artery vessel segmentation provided by an embodiment of the present application;

[0045] Figure 8 Schematic diagram of the hierarchical processing process provided by an embodiment of the present application;

[0046] Figure 9 Schematic diagram of the combined use of BioBERT and CRF models provided by an embodiment of the present application;

[0047] Figure 10 Schematic diagram of the blood pressure health management system provided by an embodiment of the present application;

[0048] Figure 11 Schematic diagram of the structure of the electronic device provided by an embodiment of the present application. Detailed implementation manners

[0049] Next, the technical solutions in the embodiments of the present application will be described in conjunction with the accompanying drawings in the embodiments of the present application. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architectures, functions, and operations of systems, methods, and computer program products according to multiple embodiments of the present invention. In this regard, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code, and the module, program segment, or part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order from that marked in the accompanying drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and the combination of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system for performing the specified functions or actions, or can be implemented by a combination of dedicated hardware and computer instructions. In addition, the functional modules in various embodiments of the present invention may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

[0050] Hypertension is a common chronic disease, which refers to the continuous elevation of arterial blood pressure at rest, usually represented by the values of systolic blood pressure and diastolic blood pressure. It is an important risk factor for cardiovascular diseases and may lead to serious health problems such as heart disease, stroke, and kidney damage. The occurrence of hypertension is related to multiple factors, including genetics, obesity, poor diet, lack of exercise, stress, and age. Since hypertension often has no obvious symptoms, it is crucial to monitor blood pressure regularly. Early detection and taking corresponding intervention measures can effectively control the condition and reduce the risk of complications.

[0051] Hypertension, as a common chronic disease, seriously affects people's quality of life and health level. Therefore, effective management and monitoring means are needed. To address this challenge, various blood pressure management platforms have emerged to achieve the monitoring and management of users' blood pressure. Currently, blood pressure management platforms are mainly divided into two types: those for general users and those for hypertension patients. The blood pressure management platform for general users mainly focuses on providing basic blood pressure monitoring and health management functions, usually including blood pressure recording, data analysis, and health reminders, aiming to help users develop good living habits, monitor their own blood pressure changes, and identify potential health problems at an early stage. The management platform for hypertension patients usually combines clinical data to provide detailed blood pressure monitoring, medication management, and dietary advice to help patients control their blood pressure more effectively.

[0052] The inventors have found through research that the current blood pressure management platforms lack a unified management platform that can take into account both general users and hypertension patients, resulting in the inability to systematically manage the management of general users and hypertension patients. The lack of a unified platform makes it difficult for patients to have a coherent health record between general users and hypertension management, affecting the medical service providers' understanding of the overall condition of patients when making treatment decisions. In addition, the existing systems fail to effectively distinguish the needs of different patients, resulting in insufficient personalized guidance and support, which in turn affects the effectiveness of health management.

[0053] Based on this, the present application proposes a blood pressure health management method and platform. This blood pressure health management method can manage both general users and hypertension patients simultaneously and can provide personalized guidance for different patients, including various medical intervention suggestions for hypertension patients, such as evaluating whether a patient is suitable for undergoing RDN surgery, RDN surgery guidance, and pre-operative and post-operative health management plans, etc. Thus, it can not only expand the scope of patient screening for RDN surgery but also detect patients at an early stage of hypertension, help them effectively control the development of the disease, and thus improve the overall treatment effect and quality of life of patients.

[0054] Please refer to Figure 1 , Figure 1 which is the flowchart of the blood pressure health management method provided by the embodiments of the present application; the present application provides a blood pressure health management method, which can be executed by an Figure 11 electronic device. This blood pressure health management method is applied to multiple target users associated with at least one blood pressure monitoring device.

[0055] This blood pressure health management method includes the following steps:

[0056] Step S100: Obtain at least one piece of blood pressure data of the target user from the target user database.

[0057] Among them, the blood pressure data includes the blood pressure data monitored by a blood pressure monitoring device.

[0058] In the above step S100, at least one piece of blood pressure data about the target user is obtained from the target user database.

[0059] At least one piece of blood pressure data of the target user includes the blood pressure data detected by the blood pressure monitoring device associated with the target user. This blood pressure monitoring device can be an autonomous blood pressure monitoring device (home blood pressure monitor) used by the user independently, such as a wrist blood pressure monitor, an arm blood pressure monitor, etc. The blood pressure monitoring device can also be a professional device used in a hospital or a blood pressure monitoring device recognized by a hospital, such as a clinical blood pressure monitor, a multi-functional monitor, etc.

[0060] In the embodiments of the present application, the blood pressure data can include the most basic blood pressure indicators (systolic blood pressure, diastolic blood pressure, and pulse parameters), professional blood pressure diagnosis information given by the medical staff side, professional cardiovascular diagnosis information given by the medical staff side, etc. In some embodiments, the blood pressure data can include data such as mean arterial pressure that can observe and evaluate the blood pressure level.

[0061] In the above implementation process, the blood pressure monitoring device is a device that has been bound with the target user information and can upload the collected user blood pressure data to the target user database. Or it is the diagnosis information (including blood pressure diagnosis information and cardiovascular diagnosis information, etc.) actively uploaded by the doctor side to the target user database.

[0062] Step S200: Manage the target user based on at least one piece of blood pressure data and generate a blood pressure health management suggestion for the target user.

[0063] In the above step S200, user management is performed based on the obtained blood pressure data, and a personalized blood pressure health management suggestion is generated. In the embodiments of the present application, the target user includes ordinary users and patient users, that is, the blood pressure health management method provided in the embodiments of the present application can manage both ordinary users and patient users at the same time.

[0064] The blood pressure health management suggestion for the target user is a personalized blood pressure health management suggestion for the target user, such as diet, exercise, drug management, and ablation surgery suggestions in specific situations. For example, assuming that the analysis of the target user's blood pressure data finds that their blood pressure has been at a high level for a long time, suggestions on drug use and lifestyle adjustment may be provided, or it may be recommended to conduct an RDN surgery evaluation.

[0065] It is understandable that RDN (Renal Denervation) is a minimally invasive treatment method for treating refractory hypertension. This surgery reduces the nerve's regulation of blood pressure by ablating the sympathetic nerves around the renal artery, thereby lowering the blood pressure level. At present, RDN is considered suitable for those hypertensive patients who do not respond well to traditional drug treatments. The goal of the surgery is to improve blood pressure control and reduce cardiovascular risks. Due to its minimally invasive nature, RDN usually has a relatively quick recovery, and patients can resume their daily activities relatively quickly after the surgery, becoming an important treatment option in the field of hypertension management.

[0066] By Figure 1 It can be seen that the blood pressure health management method provided by the embodiments of the present application can manage both ordinary users and patient users at the same time, manage target users according to at least one piece of patient's blood pressure data, and give targeted suggestions to the target users; it can not only expand the scope of patient screening applicable to RDN surgery, but also detect patients in the early stage of hypertension, help them effectively control the development of the disease, thereby helping to control blood pressure and improve health conditions.

[0067] In an optional embodiment, in the blood pressure health management method provided by the present application, the blood pressure monitoring device includes an autonomous blood pressure monitoring device, the blood pressure data includes the user-end blood pressure data corresponding to the autonomous blood pressure monitoring device, and the target users include ordinary users.

[0068] The above step S200 manages the target users based on at least one piece of blood pressure data and generates blood pressure health management suggestions for the target users, which can be achieved in the following way: manage ordinary users according to at least one piece of user-end blood pressure data and generate actionable blood pressure health management suggestions for ordinary users.

[0069] That is to say, for ordinary users, the blood pressure health management method provided by the embodiments of the present application can manage an ordinary user according to at least one of the user-end blood pressure data collected by the autonomous blood pressure monitoring device associated with the ordinary user and uploaded to the target user database, and give corresponding actionable blood pressure health management suggestions according to the specific situation of the ordinary user, which is convenient for ordinary users to implement in daily life and helps them manage blood pressure more effectively and improve overall health conditions.

[0070] Optionally, please refer to Figure 2 , Figure 2 which is the flowchart for managing ordinary users provided by the embodiments of the present application; for ordinary users, the above step S200 manages ordinary users according to at least one piece of user-end blood pressure data and generates actionable blood pressure health management suggestions for ordinary users, which can be achieved through the following steps:

[0071] Step S211: Determine the blood pressure reference level of the ordinary user based on at least one piece of user-end blood pressure data.

[0072] In the above step S211, at least one of the user-side blood pressure data collected by the autonomous blood pressure monitoring device associated with the ordinary user and uploaded to the target user database is used to determine the blood pressure reference level of the ordinary user.

[0073] It should be noted that the blood pressure reference level in the embodiments of the present application is a reference blood pressure level classification given based on the blood pressure data of the patient, and cannot represent a professional blood pressure diagnosis. In the embodiments of the present application, the blood pressure reference level includes an ideal blood pressure level, a borderline hypertension blood pressure level, and a hypertension warning blood pressure level.

[0074] Among them, the ideal blood pressure level indicates that the blood pressure condition of the target user is good and within the normal range. Exemplarily, systolic blood pressure (SBP) < 130 mmHg and diastolic blood pressure (DBP) < 85 mmHg can be considered as the ideal blood pressure level.

[0075] The borderline hypertension blood pressure level indicates that the blood pressure is already on the high side and may develop into hypertension in a short time. Exemplarily, when the systolic blood pressure is in the range of 130 - 139 mmHg and the diastolic blood pressure is in the range of 85 - 89 mmHg, it can be considered as the borderline hypertension blood pressure level.

[0076] The hypertension warning blood pressure level indicates that the blood pressure is already within the blood pressure range of hypertension and attention needs to be paid. Exemplarily, when the systolic blood pressure is in the range of 140 - 159 mmHg and the diastolic blood pressure is in the range of 90 - 99 mmHg, or when the systolic blood pressure ≥ 160 mmHg and the diastolic blood pressure ≥ 100 mmHg, it can be considered to belong to the hypertension warning blood pressure level.

[0077] Step S212(a): If it is determined that the blood pressure reference level of the ordinary user is the ideal blood pressure level, then push hypertension publicity information to the ordinary user.

[0078] In the above step S212(a), when it is determined that the blood pressure reference level of the ordinary user is the ideal blood pressure level, push hypertension publicity information to the ordinary user to help them maintain a healthy lifestyle.

[0079] In the embodiments of the present application, the hypertension promotion information that can be pushed includes: an introduction to the potential risks of hypertension such as heart disease, stroke, and kidney disease; emphasizing the importance of regularly monitoring blood pressure to understand one's own health status; providing dietary suggestions of low-salt diet and diet rich in fruits and vegetables, and recommending the DASH diet (Dietary Approaches to Stop Hypertension); emphasizing the benefits of regular exercise and suggesting at least 150 minutes of moderate-intensity aerobic exercise per week; providing lifestyle adjustment suggestions of reducing alcohol intake, quitting smoking, and maintaining a healthy weight; sharing stress relief techniques such as meditation, deep breathing, and yoga practice; reminding users of the importance of taking antihypertensive medications as prescribed by a doctor; and encouraging users to seek medical treatment regularly, especially to adjust the treatment plan in a timely manner when blood pressure is abnormal, etc. The hypertension promotion information can help users better understand hypertension and its management, thus promoting the formation of a healthy lifestyle.

[0080] Step S212(b): If it is determined that the blood pressure reference level of an ordinary user is the borderline hypertension blood pressure level, push lifestyle intervention suggestions for blood pressure reduction and medical treatment suggestions to the ordinary user.

[0081] In the above step S212(b), if it is determined that the blood pressure reference level of an ordinary user is the borderline hypertension blood pressure level, lifestyle intervention suggestions for blood pressure reduction will be provided to the ordinary user, and it is recommended that they seek medical treatment for further evaluation.

[0082] In the embodiments of the present application, the lifestyle intervention suggestions for blood pressure reduction that can be pushed may include: following a low-salt diet, increasing the intake of foods rich in fruits, vegetables, and whole grains, and recommending the DASH diet; maintaining a moderate weight, encouraging at least 150 minutes of moderate-intensity aerobic exercise per week, such as brisk walking, swimming, or cycling; reducing alcohol intake and quitting smoking to reduce cardiovascular risks; cultivating good sleep habits to ensure sufficient sleep; and learning stress management techniques such as meditation, deep breathing, and yoga to help reduce blood pressure. Providing the above intervention measures to the ordinary user helps improve the overall health status and reduce the risk of hypertension.

[0083] Step S212(c): If it is determined that the blood pressure reference level of an ordinary user is the hypertension warning blood pressure level, push a medical treatment warning message to the target user.

[0084] In the above step S212(c), if it is determined that the blood pressure reference level of an ordinary user is the hypertension warning blood pressure level, a medical treatment warning message will be pushed to the user, reminding them to seek professional medical help in a timely manner.

[0085] In the embodiments of the present application, the medical warning information may include: if the user's blood pressure continuously stays within the hypertension warning range (such as systolic blood pressure ≥ 140 mmHg or diastolic blood pressure ≥ 90 mmHg), it is recommended that the user immediately contact a doctor; when symptoms such as headache, blurred vision, chest pain, or difficulty breathing occur, remind the user to seek medical attention as soon as possible; inform the user that when the blood pressure rises and is accompanied by severe discomfort, such as rapid heartbeat or palpitations, they should immediately go to the emergency department; in addition, it is recommended that the user regularly monitor their blood pressure and seek medical attention in a timely manner when abnormal changes are found to ensure professional medical evaluation and necessary treatment. The medical warning information pushed to the user in the embodiments of the present application aims to prompt the user to stay vigilant about their own health status and take actions in a timely manner.

[0086] It can be seen from Figure 2 that the blood pressure health management method provided by the embodiments of the present application can effectively manage the user's blood pressure health by systematically analyzing the blood pressure data of ordinary users. First, by determining the user's blood pressure reference level, the health status of the user is identified, and then personalized suggestions are provided. For example, for users with normal blood pressure, the system pushes hypertension publicity information to consolidate healthy habits; for users with borderline blood pressure, intervention suggestions for blood pressure-lowering lifestyles are provided and medical treatment is recommended; for users with blood pressure warnings, medical warning information is pushed in a timely manner to ensure that they can quickly obtain professional medical help. The dynamic management and targeted suggestions for ordinary users not only enhance the user's health awareness but also promote early intervention, ultimately contributing to improving the overall health status and reducing hypertension-related risks.

[0087] Please refer to Figure 3 , Figure 3 which is a schematic diagram of an ordinary user being converted into a patient user provided by the embodiments of the present application; in an alternative embodiment of the embodiments of the present application, the target user also includes patient users. The blood pressure data also includes hypertension diagnosis information. The step of managing ordinary users according to at least one piece of user-side blood pressure data in the above step S200 further includes the following: determining an ordinary user as a patient user according to the user-side blood pressure data and hypertension diagnosis information.

[0088] It should be noted that the hypertension diagnosis information is the information provided by the medical staff side and is fed back to the target user database after the patient seeks medical treatment.

[0089] Based on the user-side blood pressure data and hypertension diagnosis information, comprehensively analyze and determine whether an ordinary user should be classified as a patient user, more accurately identify those users who have been diagnosed with hypertension, and thus provide them with more personalized management and guidance.

[0090] In the embodiments of the present application, for users identified as patients, lifestyle adjustments, medication management, and regular check-up recommendations suitable for their conditions can be recommended, thereby effectively controlling the development of the condition and improving the overall health of the users.

[0091] As Figure 3 shown, ordinary users actively go to the hospital for medical treatment, and the hospital assigns the patients to the corresponding doctors; the doctors actively retrieve the relevant data of the user from the target user database (cloud) and make a diagnosis. After the doctor analyzes the blood pressure data and hypertension diagnosis information, comprehensively analyzes and determines whether the ordinary user should be classified as a patient user; finally, the doctor converts the ordinary user who needs to be classified as a patient user into a registered patient user, thus completing the conversion of the ordinary user into a registered patient.

[0092] It can be seen that the blood pressure health management method provided by the embodiments of the present application can effectively identify users who have been diagnosed with hypertension by analyzing the blood pressure data and diagnosis information of the users, and convert the user from an ordinary user to a patient user, so as to provide personalized management suggestions and intervention measures for them. It ensures a clear boundary between ordinary users and patient users, enables patients to obtain targeted lifestyle adjustments, medication management, and regular check-up recommendations, effectively controls the development of the condition, and improves the overall health. On the other hand, this dynamic management mechanism not only enhances the health awareness of users, but also provides more detailed data support for medical staff, helps them make more scientific treatment decisions, and ultimately improves the overall effect of hypertension management.

[0093] In an optional embodiment, in the above step S200, at least based on at least one blood pressure data, manage the target user and generate a blood pressure health management recommendation for the target user, and further include the following steps: according to the blood pressure data, push medical intervention recommendations to the patient user.

[0094] The medical intervention recommendations in the above process may include: recommending a specific drug treatment plan, adjusting the existing treatment plan, suggesting further medical examinations or tests, and even including whether specific treatments such as renal denervation (RDN) surgery are suitable; in some possible cases, the above medical intervention recommendations can comprehensively consider the diagnosis information at the medical staff side.

[0095] It can be seen that the blood pressure health management method provided by the embodiments of the present application can not only provide real-time and professional guidance for patient users, but also improve the patients' awareness and management ability of their own conditions. Timely medical intervention recommendations can promote patients to comply with medical advice, improve the treatment effect, and reduce the risk of complications caused by out-of-control blood pressure.

[0096] In an optional embodiment, please refer to Figure 4 , Figure 4The flowchart of patient user management provided by the embodiments of the present application; The above-mentioned pushing medical intervention suggestions to patient users based on blood pressure data can be achieved through the following steps:

[0097] Step S221: Determine the clinical blood pressure level of the patient user according to the blood pressure data of the user terminal and the hypertension diagnosis information.

[0098] In the above step S221, the clinical blood pressure level of the patient user is determined according to the blood pressure data of the user terminal and the hypertension diagnosis information generated by the medical staff terminal. It should be noted that in the embodiments of the present application, the clinical blood pressure level is evaluated by medical staff according to the patient's blood pressure data and relevant diagnosis information (such as hypertension diagnosis information) after the patient seeks medical treatment.

[0099] Among them, the clinical blood pressure level includes the moderate-to-severe hypertension level. The moderate-to-severe hypertension level represents that the blood pressure is already relatively high. Exemplarily, when the systolic blood pressure ≥ 160 and the diastolic blood pressure ≥ 100 mmHg, it can be considered as the moderate-to-severe hypertension level.

[0100] Step S222(a): If it is determined that the clinical blood pressure level of the patient user is the moderate-to-severe hypertension level, then push a medication warning message to the patient user.

[0101] In the above step S222(a), if it is determined that the patient's clinical blood pressure level is the moderate-to-severe hypertension level, then push a medication warning message to the patient user. The medication warning reminds the patient that their hypertension needs to be controlled with medications.

[0102] In an optional embodiment, among them, the blood pressure data further includes cardiovascular diagnosis information; the clinical blood pressure level further includes the normal high-value blood pressure level and the mild hypertension level.

[0103] The normal high-value blood pressure level refers to the upper limit of the normal range of the patient's blood pressure level. Usually, the systolic blood pressure is between 130 - 139 mmHg or the diastolic blood pressure is between 85 - 89 mmHg. This means that although the blood pressure has not reached the hypertension standard, it is already close to the boundary of hypertension and requires attention to health management.

[0104] The mild hypertension level indicates that the patient's blood pressure level is slightly higher than the normal range. Usually, the systolic blood pressure is between 140 - 159 mmHg or the diastolic blood pressure is between 90 - 99 mmHg. The patient may face the risk of hypertension and needs to take measures for monitoring and intervention to prevent the condition from deteriorating further.

[0105] The above-mentioned pushing medical intervention suggestions to patient users based on blood pressure data further includes:

[0106] Step S222(b): If it is determined that the clinical blood pressure level of the patient user is in the normal high value blood pressure level or the mild hypertension level, generate blood pressure health management suggestions for the patient user based on the cardiovascular diagnosis information of the patient user.

[0107] In the above step S222(b), if the patient's clinical blood pressure level is in the normal high value or mild hypertension, it is necessary to further evaluate their cardiovascular status; based on the cardiovascular diagnosis information of the patient user, generate personalized blood pressure health management suggestions.

[0108] In the above implementation process, if the patient's clinical blood pressure level is in the normal high value or mild hypertension, it is crucial to further evaluate their cardiovascular status, because although these blood pressure levels have not reached the hypertension standard, they are already close to the risk range and may affect cardiovascular health. Cardiovascular diagnosis information can reveal the patient's overall cardiovascular risk, including whether there are other potential diseases, such as coronary heart disease, heart failure or stroke risk, etc. By comprehensively considering the blood pressure level and cardiovascular status, the blood pressure health management suggestions provided by doctors are more accurate.

[0109] Step S222(c): In the case where the clinical blood pressure level of the patient user is in the normal high value blood pressure level and the cardiovascular diagnosis information is low-risk or medium-risk; or, in the case where the clinical blood pressure level of the patient user is in the mild hypertension level and the cardiovascular diagnosis information is low-risk; generate lifestyle intervention suggestions for blood pressure reduction.

[0110] In the above step S222(c), when the clinical blood pressure level of the patient user is in the normal high value and the cardiovascular diagnosis information is low-risk or medium-risk, or the clinical blood pressure level is in the mild hypertension and the cardiovascular diagnosis information is low-risk, generate lifestyle intervention suggestions for blood pressure reduction.

[0111] Although the normal high value blood pressure and mild hypertension have not reached the hypertension diagnosis standard, they have significantly increased the risk of cardiovascular diseases. At this time, the patient's cardiovascular status is evaluated as low-risk or medium-risk, indicating that the patient still has a good cardiovascular health foundation to a certain extent. Therefore, through lifestyle interventions, such as improving diet, increasing exercise, controlling weight, etc., it is possible to effectively reduce blood pressure and reduce the risk of developing hypertension or cardiovascular diseases in the future.

[0112] On the other hand, implementing lifestyle intervention measures is the preferred strategy for non-drug treatment, which can regulate blood pressure in a natural way and have a positive impact on the patient's overall health. It not only helps the patient establish healthier living habits, but also improves their sense of participation and responsibility in their own health management.

[0113] Step S222(d): Generate a medication recommendation when the cardiovascular diagnosis information of the patient user is at the normal high blood pressure level and the cardiovascular diagnosis information is at high risk or very high risk.

[0114] In the above step S222(d), when the clinical blood pressure level of the patient user is at the normal high value and the cardiovascular diagnosis information shows high risk or very high risk, a medication recommendation is generated.

[0115] That is to say, even if the patient's blood pressure is within the normal high value range, but if accompanied by high-risk or very high-risk cardiovascular diagnosis information, it indicates that the patient may face a serious risk of cardiovascular events. In this case, relying solely on lifestyle adjustments may not be sufficient to effectively control blood pressure or reduce the probability of cardiovascular events. Therefore, drug treatment is needed. Drug treatment can effectively reduce blood pressure in a shorter time and reduce the risk of cardiovascular events such as heart disease and stroke; especially for those patients with other cardiovascular risk factors, timely drug intervention is an important measure to prevent the deterioration of the condition.

[0116] Step S222(e): Generate a medication warning message when the cardiovascular diagnosis information of the patient user is at the mild hypertension level and the cardiovascular diagnosis information is at moderate risk or high risk or very high risk.

[0117] In the above step S222(e), when the cardiovascular diagnosis information of the patient user is at the mild hypertension level and at the same time faces moderate, high or very high risk, a medication warning message is generated. Although mild hypertension does not reach the standard of hypertension, but accompanied by a moderate to high-risk cardiovascular status, it indicates that the patient's cardiovascular health is potentially threatened. In this case, drug treatment is necessary, and the medication warning message reminds the patient to take medication as soon as possible in the current state.

[0118] In the above implementation process, the cardiovascular diagnosis information is divided into: low risk, moderate risk, high risk and very high risk.

[0119] Low risk, the patient has no obvious symptoms of cardiovascular disease, the health indicators are normal, the risk is low, and usually maintains a good state through a healthy lifestyle.

[0120] Moderate risk, the patient has minor cardiovascular risk factors (such as mild hypertension, family history, etc.), and needs to pay attention to management to prevent future risk increase.

[0121] High risk, the patient has obvious risk factors (such as moderate hypertension, diabetes, etc.), and needs active treatment and lifestyle adjustments to reduce the risk of cardiovascular events.

[0122] Very high risk. The patient already has a confirmed cardiovascular disease or serious abnormal indicators, facing an extremely high risk, and requires urgent and comprehensive medical intervention to stabilize cardiovascular health.

[0123] Through Figure 4 It can be seen that when the patient's blood pressure is at the normal high value or mild hypertension level, the blood pressure health management method provided by the embodiments of the present application combines the cardiovascular conditions and provides corresponding lifestyle intervention or drug treatment suggestions to ensure timely health management. Thus, it can be known that the blood pressure health management method provided by the embodiments of the present application is a dynamic management method based on risk assessment, which not only improves the patient's sense of participation in health management, but also effectively prevents the occurrence of cardiovascular events and optimizes the overall treatment effect.

[0124] Please continue to refer to Figure 4 , in an optional embodiment, the blood pressure health management method of the present application further includes the following steps:

[0125] After generating the medication warning information or medication advice (after steps S222(a), S222(d), S222(e)), step S223(a): According to the blood pressure data of the patient user corresponding to the generated medication warning information or medication advice within a preset time period, determine whether the patient user is a patient with poor drug control.

[0126] In the above step S223(a), determining whether the user is a patient with poor drug control includes: After standard treatment with two or more antihypertensive drugs for one month, the blood pressure is still not controlled (clinic blood pressure ≥ 150 / 90 mmHg and 24h ASBP ≥ 135 mmHg), or, being refractory hypertension, that is, a patient whose blood pressure is not well controlled after treatment with three different classes of antihypertensive drugs (including one diuretic) for more than three months.

[0127] And, step S223(b): In the case of generating the medication warning information or medication advice, determine whether the corresponding patient user is a patient who cannot use drugs.

[0128] In the above step S223(b), in the embodiments of the present application, patients with poor compliance with antihypertensive treatment or intolerance to multiple types of antihypertensive drugs, resulting in ineffective blood pressure control, are all identified as patients who cannot use drugs.

[0129] Step S224: If the patient user is a patient with poor drug control or a patient who cannot use drugs, generate an ablation surgery recommendation.

[0130] In the above step S224, if the patient is determined to be a patient with poor drug control or a patient who cannot use drugs, an ablation surgery recommendation will be provided for the patient to effectively treat hypertension in the case of ineffective drug treatment or inability to perform drug treatment.

[0131] Step S225: After confirming through the pre-operative planning scheme that the patient user will undergo ablation surgery, determine the patient user as the surgical user and generate a surgical planning recommendation for the surgical user.

[0132] In the above step S225, after confirming through the pre-operative planning scheme that the patient will undergo surgery, convert the patient user into a surgical user and generate a surgical planning recommendation for the surgical user.

[0133] It should be noted that in the embodiments of the present application, the pre-operative planning scheme includes communicating with the patient, informing the possible benefits, risks and current limitations of RDN, whether the patient agrees to undergo ablation surgery, and also includes the medical staff side confirming whether the patient is suitable for ablation surgery.

[0134] The ways for the medical staff side to confirm whether the patient is suitable for ablation surgery include: clarifying indications and contraindications. Screening and excluding secondary hypertension, and clarifying the renal artery anatomical structure and renal function suitable for RDN treatment through renal function examination, renal artery CT or MRI or renal artery ultrasound.

[0135] It can be seen that in the blood pressure health management method of the embodiments of the present application, when the patient is determined to have poor drug control or be unable to use drugs, ablation surgery recommendations are generated in a timely manner to ensure that the patient can still obtain effective hypertension management when the drug treatment effect is not ideal. At the same time, the implementation of the pre-operative planning scheme not only communicates fully with the patient to clarify the benefits and risks of the surgery, but also ensures that the patient's indications and contraindications are accurately identified through the confirmation of the medical staff side, thereby optimizing the treatment plan and improving the safety and treatment effect of the patient.

[0136] Please refer to Figure 5 and Figure 6 , Figure 6 , which is the training block diagram of the surgical planning model provided by the embodiments of the present application; Figure 5 , which is the flowchart for generating the surgical planning recommendation provided by the embodiments of the present application; In an optional embodiment, in the above step S225, the generation of the surgical planning recommendation for the surgical user can be achieved through the following steps:

[0137] Step S10: According to the pre-operative image data, identify the tissue morphology and tissue size of the target tissue of the surgical user.

[0138] In the above step S10, identify the tissue morphology and tissue size of the target tissue of the surgical user according to the pre-operative image data.

[0139] The pre-operative image data includes CTA, CT, MRI and / or US images of the target ablation area to obtain detailed structural information of the patient's target tissue.

[0140] Step S20: Generate a patient information report based on the basic patient information of the surgical user.

[0141] In the above step S20, collect the diagnostic report and the basic information of the patient, such as height, weight, genetic history, and allergy history, etc. Generate a patient information report according to the basic patient information. Exemplarily, first perform data cleaning and missing value filling. Then, extract the key information from the diagnostic text to provide support for subsequent analysis. Next, construct a neural network using a language model (such as a Transformer network), and the processed data will be divided into a dataset for training and generating a patient information report.

[0142] Step S30: Determine the standard blood pressure level of the surgical user based on the preoperative quantitative data.

[0143] In the above step S30, determine the standard blood pressure level of the surgical user based on the preoperative quantitative data. Among them, the preoperative quantitative data includes data such as the 24-hour blood pressure, heart rate, and blood sugar of the surgical patient, and a final standard blood pressure level is evaluated based on these data. It should be noted that the determined standard blood pressure level at this time can affect the planning of the ablation surgery.

[0144] Step S40: Determine the planned ablation location, planned ablation points, planned ablation time, and planned operation duration of the surgical user according to the tissue morphology, tissue size, standard blood pressure level, the patient information report of the surgical user, and the historical ablation surgery planning scheme.

[0145] In the above step S40, according to the previously obtained tissue morphology, tissue size, standard blood pressure level, patient information report, and its historical ablation surgery plan, the doctor formulates a detailed surgical plan. Among them, the planned ablation location clarifies the specific part of the ablation operation, such as the renal artery branch or the main renal artery. The planned ablation points determine the precise location and the number of locations for ablation. The planned ablation time is to estimate the time required for the ablation process to reasonably arrange the surgical process. The planned operation duration is to predict the duration of the entire operation to facilitate the reasonable allocation of resources and postoperative management.

[0146] Steps S10 - S40 provided by the embodiments of the present application can be implemented relying on a surgical planning model. Please refer to Figure 5 and Figure 6 on the basis of Figures 7 - 9 , Figure 7 is a schematic diagram of segmenting renal artery blood vessels using the UNet3D network model provided by the embodiments of the present application; Figure 8 is a schematic diagram of the hierarchical processing process provided by the embodiments of the present application; Figure 9Schematic diagram of the combined use of BioBERT and CRF models provided by the embodiments of the present application; The present application provides a surgical planning model training method, and the surgical planning model training method includes:

[0147] Please refer to Figure 6 on the basis of Figure 7 , for the above step S10, first, collect case data in the database, including a variety of important contents. Step S11: In terms of image data, obtain CTA, CT, MRI, and / or US images to understand the morphological information of the patient's renal artery vessels in detail. Quantitative data includes health indicators such as the patient's blood pressure, heart rate, and blood sugar. At the same time, diagnostic reports and the patient's basic information, such as height, weight, genetic history, and allergy history, also need to be collected. In addition, surgical process data, such as the number of ablation points, ablation sites, total ablation time, and surgical duration, etc., provides reference for surgical planning and execution. Step S12: For the image data, first perform annotation to identify the morphology of the renal artery vessels, and two-dimensional or three-dimensional marking methods can be used. Step S13: Subsequently, perform data preprocessing, including data cleaning and data augmentation, etc., to improve the quality of the model training data. Step S14: In the training of the deep learning model, build an image recognition and segmentation model (such as CNNs or transformer networks), Step S15: Divide the annotated data into a training set and a test set for model training; Step 16: Perform model evaluation and prediction to determine the final prediction model. After the imaging data is processed by deep learning, the outline of the renal artery can be generated. Step S17: Subsequently, through data post-processing, extract the diameter information of each segment of the blood vessel and the morphological outline of the blood vessel (represented by coordinate points).

[0148] For the above step S14, for the image data in the database, deep learning models can be used for processing. For example, 2D network models and 3D network models based on UNet, 2D network models and 3D network models based on transfromer, and network models based on multi-modal data fusion. Among them, the UNet3D network model has good generalization ability for medical images, and at the same time, the training of the model does not require a large amount of computing resources. As Figure 7 shown, the overall framework includes an input, an encoder, a decoder, skip connections, and an output layer.

[0149] Optionally, please refer to Figure 7 for an example of using the UNet3D network model to segment blood vessels from 3D renal artery CT image data.

[0150] The input is a three-dimensional CT image block with a size of (N, N, L, Channels), where N is the axial resolution, L is the number of longitudinal slices, and Channels is usually 1 (gray single channel).

[0151] The encoder is composed of 4 stacked downsampling modules. Each module sequentially includes a 3D convolution (Conv3D, kernel size 3×3×3, padding='same'), batch normalization (BatchNorm3D), ReLU activation function, and max pooling layer (MaxPool3D, kernel size 2×2×2). The initial number of channels starts from 64, and the number of channels doubles after each level of downsampling while the spatial dimensions (in the N and L directions) are halved. Finally, a feature map with a size of (N / 16×N / 16×L / 16×512) is output at the fourth level. The encoder gradually compresses spatial information through hierarchical downsampling while extracting multi-scale local features of blood vessels (such as changes in vessel diameter, branch topology, etc.), providing high-semantic abstract features for the subsequent decoder.

[0152] The bridging layer, which is located between the encoder and the decoder, consists of two consecutive 3D convolution modules (Conv3D - BatchNorm - ReLU) with the number of channels remaining unchanged at 512. The role of this layer is to further fuse the high-level semantic features output by the encoder, enhance the model's ability to represent complex blood vessel structures (such as the continuity of small branches), and at the same time provide richer context information for the feature reconstruction of the decoder through non-linear transformation.

[0153] The decoder contains 4 upsampling modules. Each level doubles the spatial dimension through transposed convolution (Conv3DTranspose, kernel size 2×2×2, stride = 2), and then concatenates the feature maps output by the encoder at the same level in the channel dimension through skip connections. The concatenated features are fused through two 3D convolution modules (Conv3D - BatchNorm - ReLU), and the number of channels is halved level by level (from 512 to 64). The core goal of the decoder is to gradually restore the spatial resolution through upsampling while using skip connections to fuse shallow details (such as blood vessel edges) and deep semantic information (such as blood vessel topology), and finally output a feature map with the same size as the input (N×N×L).

[0154] The output layer uses a 3D convolution layer with a size of 1×1×1 at the end of the model to map the number of channels to the number of target classes (NumClass = 2, corresponding to blood vessels and background), and generates a probability map of each voxel belonging to blood vessels through the Sigmoid activation function. This process retains spatial information through a fully convolutional structure, avoiding the problem of parameter explosion introduced by fully connected layers. At the same time, the Sigmoid function constrains the output to the [0,1] interval, facilitating subsequent thresholding to generate a binary segmentation mask.

[0155] In addition, during the model evaluation stage (step S16), the Dice Score function can be used to evaluate the quality of the model in segmenting blood vessels.

[0156] Meanwhile, for step S30 above, please refer to Figure 6 on the basis of Figure 8 , step S31: First, obtain quantitative data such as blood pressure, heart rate, and blood sugar for 24 hours; step S32: For the patient's quantitative data (blood pressure, heart rate, blood sugar, etc.), perform cleaning, missing value filling, and normalization processing, extract hierarchical features and classify them; steps S33 and S34: Finally, select an appropriate pre-set machine learning model (such as support vector machine, decision tree, random forest, etc.) for training and evaluation to generate corresponding classification results; step S35: According to the classification results, divide the levels from high to low blood pressure; step S36: Finally, output the classification result (i.e., the standard blood pressure level of the surgical user).

[0157] Exemplarily, as Figure 8 shown, for the obtained data such as blood pressure, heart rate, blood sugar, electrocardiogram, etc., denote (X1i, X2i, X3i, X4i,... Xji), where (i, j = 1, 2, 3, 4,... n); first process the data, including data missing processing, data smoothing, data normalization, etc. (steps S31 and S32), then input the data into the machine learning model, output the classification results (Y1i, Y2i, Y3i, Y4i,...) of each feature, and then perform weighted and bias processing on the results and use the activation function to obtain the predicted classification result And set the loss function L and the gradient descent function to update the parameters, and repeat the iterative calculation until convergence or the maximum number of iterations is reached (steps S33 to S36).

[0158] Figure 8 The machine learning model in (the machine learning model in step S33) can select a logistic regression model, decision tree, support vector machine, XGBoost, LightGBM, etc. The forward propagation prediction result formula:

[0159] In the embodiment of the present application, the mean squared error loss function is preferably selected. The mean squared error loss function formula is The gradient descent function can select a stochastic gradient descent function, batch gradient descent function, momentum gradient descent function, Adam gradient descent function, etc. In the embodiment of the present application, the stochastic gradient descent function is preferably selected for parameter update, and the parameter update strategy of the stochastic gradient descent function is as follows:

[0160]

[0161] Among them, μ represents the learning rate, which represents the step size of parameter update.

[0162] Regarding the above step S20, please refer to Figure 6 on the basis of Figure 9 , when processing the diagnostic report and patient information (including height, weight, genetic history, allergy history, etc.), step S21: Obtain the diagnostic report and patient information (including height, weight, genetic history, allergy history, etc.), step S22: First, perform preprocessing such as data cleaning and missing value filling. Step S23: Then, extract the patient information features of the preprocessed patient basic information, and extract the key information in the diagnostic text to provide support for subsequent analysis. Steps S24 to S27: Next, based on the target neural network model, obtain the patient information report. A neural network can be constructed using a language model (such as a Transformer network), and the processed data will be divided into data sets for training and generating the patient information report.

[0163] Exemplarily, please refer to Figure 9 , for the input diagnostic report, patient information and other data, perform data annotation and organize them into a data set, input the model for training, and output a patient information report in json format, with the format roughly as follows:

[0164] {

[0165] "Patient": ["Mr. Li"],

[0166] "Age": ["65 years old"],

[0167] "Weight": [80 kg]

[0168] "Medical history": ["Hypertension", "Up to 180 / 100 mmHg", "Down to 140 / 85 mmHg"],

[0169] "Symptoms": ["Hypertension", "Dizziness", "Fatigue", "Blood pressure out of control"],

[0170] "Examinations": ["Blood glucose 18 mmol / L", "Blood pressure 178 / 95 mmHg", "Heart rate 80 beats / minute", "ECG shows sinus rhythm, left ventricular hypertension"],

[0171] "Diagnosis result":

[0172] ["Hypertension", "Diabetes"]

[0174] "Treatment suggestions": [[ "Medication suggestions", "Amlodipine 5mg once a day", "Metformin 500mg twice a day" ], [ "Surgery suggestions", "Use RDN renal artery sympathetic denervation" ]]

[0175] ---

[0176] ---

[0177] }

[0178] Optionally, in the above implementation process, the pre-trained deep learning natural language model corresponding to the target neural network may further include: BERT variants, GPT variants, etc. BERT variants include: ClinicalBERT, BioBERT, BlueBERT; GPT variants include: BioGPT, Med-PaLM (Google), Graph Neural Networks, T5, etc.

[0179] In the embodiments of the present application, the BioBERT pre-trained model is preferably used (as Figure 9 shown), and CRF (Conditional Random Field) is added for post-processing.

[0180] First, the original input data (such as a sentence sequence) (Dataset), then feature extraction is performed to obtain E1...EN, and through the intermediate layer Trm, the initial prediction or probability distribution T1...TN of the labels is obtained; through the conditional random field layer (CRF), the adjacent label dependencies are integrated; finally, the optimal label sequence (Predict Label Sequence) is output.

[0181] Finally, in step S42 of step S40, the data in step S17, step S27, step S36, and step S41 are integrated, that is, the data generated by each sub-module (such as vascular morphology and diameter information, grading results, patient information reports, etc.) are integrated with the surgical process data (such as the number of ablation points, ablation sites, total ablation time, surgical duration, etc.) for comprehensive analysis and interpretation. Step S43: The integrated data needs to be normalized, and steps S44 to S46: and a neural network model (such as Transformer or GPT) is used for training and evaluation to predict information such as the number of ablation points, ablation sites, and total ablation time during the surgery.

[0182] Exemplarily, it is organized into a new dataset for model training, and the data type is in json format, for example:

[0183] {

[0184] "Image processing results": ["3D vascular morphology", [0, 0, 0, 0, … 0, 0], [, 0, 0, …, 0, 0], [0, 0, 0, 1, …, 0, 0], …, [0, 0, 0, 0, … 0, 0]], ["Dimensions of each branch", [3, 5, 6, 8]];

[0185] "Patient grading results": [1];

[0186] "Patient information report": {"Patient": ["Mr. Li"],

[0187] "Age": ["65 years old"], …

[0188] }

[0189] "Surgical data": ["Total number of ablation points", "48"], [[["Ablation location 1", "The secondary branch is 10 mm from the bifurcation, the lumen diameter is 5 mm, the number of ablation points is 5, and the time taken is 80 seconds"], ["Ablation location 2", "The secondary branch is 30 mm from the bifurcation, the lumen diameter is 4.5 mm, the number of ablation points is 4, and the time taken is 120 seconds"], …], ["Total ablation time", "30 minutes"], ["Total surgical duration 60 minutes"], …]

[0190] "Postoperative effect evaluation": ["Preoperative blood pressure", "180 / 89 mmHg"], ["Postoperative blood pressure on the same day", "145 / 78 mmHg"], ["Blood pressure at three-month follow-up", "136 / 72 mmHg"]

[0191] }

[0192] A deep learning multi-modal Transformer model can be used to find the relationships between various data and output surgical guidance suggestions, including the estimated surgical time, recommended ablation points, recommended ablation time for each location, and estimated postoperative effects. Among them, the multi-modal Transformer can be selected from MedCLIP, BioViL, LXMERT, Flamingo, MMBT. Preferably, the BioViL model is used.

[0193] Finally, the morphology of the patient's renal artery blood vessels, the diameters of each segment, the grading results, and the personalized information report will be output, providing a comprehensive reference for surgical planning.

[0194] When a new patient arrives, key information such as the patient's imaging images (such as CTA, CT, MRI, and / or US images), blood pressure, heart rate, blood sugar, and diagnostic reports will be collected first. These data will be input into the trained surgical planning model to generate corresponding output information, including the diameters of each segment of the blood vessels, the vascular morphology coordinate information, and the blood pressure level information.

[0195] In the actual application process of the surgical planning model provided in the embodiments of the present application, the model will be continuously optimized according to the continuously accumulated new case data.

[0196] On the one hand, as more and more patient data is input, the model can learn more diverse patient characteristics and surgical process information. These newly added data will help the model improve the recognition and prediction accuracy of renal artery vascular morphology, vascular diameter, patient health indicators, etc. through regular training and updates. At the same time, through continuously updated surgical process data (such as the number of ablation points, ablation sites, surgical duration, etc.), the model can better adapt to the individual differences of different patients and improve the personalization and accuracy of surgical planning.

[0197] On the other hand, with the in-depth application of the model, expert feedback and the accumulation of clinical experience will also become important sources for model optimization. By verifying and adjusting the model's prediction results, the model can be gradually improved in a more real-world clinical scenario, reducing errors and improving the stability of predictions. Eventually, after multiple rounds of iterative training, the model can more efficiently process the case data of new patients, not only providing more accurate vascular morphology and grading information, but also better predicting and optimizing surgical process parameters, providing more reliable decision-making support for clinicians.

[0198] Through Figure 6 It can be seen that the blood pressure health management method provided in the embodiments of the present application realizes personalized and precise surgical planning by integrating various patient data and intelligent models. The surgical planning suggestions generated using preoperative images and patient quantitative data reduce surgical risks while ensuring the effectiveness of ablation surgery. The intelligent surgical planning model further automates the data processing process and planning generation, improves the accuracy and reliability of operations, provides scientific support for medical staff, and helps with efficient and personalized blood pressure health management and surgical implementation.

[0199] In an optional embodiment, the blood pressure health management method provided in the present application further includes: monitoring at least one blood pressure data of the surgical user after the ablation surgery is performed, and pushing postoperative recovery suggestions to the patient user.

[0200] After the ablation surgery, regularly record and analyze the patient's blood pressure changes to evaluate the surgical effect and the patient's overall health status. By using remote monitoring devices, the patient's blood pressure information can be obtained in a timely manner to ensure that it is within the normal range and to detect potential complications.

[0201] Optionally, during the monitoring process, automatically identify abnormal blood pressure fluctuations and generate personalized postoperative recovery suggestions according to the specific situation of the patient.

[0202] The postoperative recovery suggestions in the embodiments of the present application may include dietary adjustments, increased exercise, and medication adjustments, etc., aiming to help patients recover better and control blood pressure. By actively pushing these recovery suggestions, patients can obtain real-time guidance and promote postoperative recovery.

[0203] It can be seen that the blood pressure health management method provided by the embodiments of the present application monitors and implements postoperative recovery suggestions after ablation surgery, which can improve the quality and safety of patients' postoperative recovery. By continuously tracking patients' blood pressure data and providing personalized recovery plans, it can not only reduce the risk of postoperative complications, but also improve patients' awareness and compliance with health management, thereby improving the long-term blood pressure control effect.

[0204] Please refer to Figure 10 , Figure 10 , which is a schematic diagram of the blood pressure health management system provided by the embodiments of the present application; the present application provides a blood pressure health management system, which includes a device management module, a user management module, and a user database.

[0205] The device management module is configured to bind the blood pressure monitoring device associated with the target user, obtain the blood pressure data measured by the blood pressure monitoring device, and store it in the user database.

[0206] The user management module is configured to manage the target user based on at least one piece of blood pressure data of the target user and push blood pressure health management suggestions to the user side.

[0207] In the above implementation process, the device management module is responsible for binding the blood pressure monitoring device associated with the target user, such as a smart bracelet or a sphygmomanometer, to ensure that the user's monitoring device can accurately identify and collect the user's blood pressure data. After the device is bound, the system will automatically obtain the real-time blood pressure data measured by these devices and store it in the user database.

[0208] The user management module analyzes based on the stored blood pressure data, identifies the user's health status and conducts corresponding management. For example, the system will judge the user's blood pressure control situation according to the user's blood pressure trend and historical records, and generate personalized health management suggestions. For the detailed types of blood pressure health management suggestions in the present application, please refer to the above text and will not be elaborated here.

[0209] Through Figure 10 It can be seen that the blood pressure health management system provided by the embodiments of the present application makes full use of the combination of the device management module and the user management module to realize the real-time monitoring and intelligent analysis of the user's blood pressure. Through automated data collection and personalized health management suggestions, the system not only improves the user's health awareness and participation, but also effectively promotes the long-term effect of blood pressure control, and finally realizes the goal of optimizing patients' health management.

[0210] In an optional embodiment, the blood pressure monitoring device includes an autonomous blood pressure monitoring device, the blood pressure data includes the user - end blood pressure data corresponding to the autonomous blood pressure monitoring device, and the target users include ordinary users; the user management module includes an ordinary user management unit, and the ordinary user management unit is configured to:

[0211] Determine the blood pressure reference level of the ordinary user based on at least one piece of user - end blood pressure data, and store the blood pressure reference level in the user database; wherein, the blood pressure reference levels include the ideal blood pressure level, the borderline hypertension blood pressure level, and the hypertension warning blood pressure level.

[0212] If it is determined that the blood pressure reference level of the ordinary user is the ideal blood pressure level, push hypertension publicity information to the user end.

[0213] If it is determined that the blood pressure reference level of the ordinary user is the borderline hypertension blood pressure level, push blood pressure - lowering lifestyle intervention suggestions and medical advice to the user end.

[0214] If it is determined that the blood pressure reference level of the ordinary user is the hypertension warning blood pressure level, push medical warning information to the user end.

[0215] In the above implementation process, the ordinary user management unit in the user management module can determine the blood pressure reference level of the user according to the blood pressure data of the user end and store it in the user database. The blood pressure reference levels are divided into ideal blood pressure, borderline hypertension, and hypertension warning levels. If the user's blood pressure level is ideal, push hypertension publicity information; if it is borderline hypertension, push blood pressure - lowering lifestyle intervention suggestions and medical advice; if it is hypertension warning, push medical warning information.

[0216] It can be seen that the blood pressure health management system provided by the embodiments of the present application can accurately judge the blood pressure reference level of the user by intelligently analyzing the user's blood pressure data, so as to realize personalized health management and intervention suggestions. It can not only improve the user's health awareness, but also guide the user to take necessary measures at critical moments, promote the formation of a healthy lifestyle, effectively prevent and control hypertension, and improve the overall health level.

[0217] In an optional embodiment, the target users further include patient users; the user management module further includes a patient user management unit.

[0218] The user management module is further configured to obtain blood pressure data including the hypertension diagnosis information of the target user from the medical staff end. When the target user is an ordinary user, convert the ordinary user into a patient user and store the hypertension diagnosis information in the user database.

[0219] The patient user management unit is configured to determine the clinical blood pressure level of the patient user based on the user-end blood pressure data and the hypertension diagnosis information; wherein, the clinical blood pressure levels include normal high-value blood pressure, mild hypertension level, and moderate-severe hypertension level; and if it is determined that the clinical blood pressure level of the patient user is the moderate-severe hypertension level, a medication warning message is pushed to the user end.

[0220] In an optional embodiment, the user management module is further configured to obtain the cardiovascular diagnosis information of the patient user including the patient user from the medical staff end and store the cardiovascular diagnosis information in the user database

[0221] The patient management unit is further configured to, when the clinical blood pressure level of the patient user is the normal high-value blood pressure level and the cardiovascular diagnosis information is low-risk or medium-risk; or, when the clinical blood pressure level of the patient user is the mild hypertension level and the cardiovascular diagnosis information is low-risk; push a blood pressure lowering lifestyle intervention suggestion to the user end.

[0222] When the cardiovascular diagnosis information of the patient user is the normal high-value blood pressure level and the cardiovascular diagnosis information is high-risk or very high-risk, a medication suggestion is pushed to the user end.

[0223] When the cardiovascular diagnosis information of the patient user is the mild hypertension level and the cardiovascular diagnosis information is medium-risk or high-risk or very high-risk, a medication warning message is pushed to the user end.

[0224] In the above implementation process, the user management module further includes a patient user management unit. The patient user management unit can obtain the hypertension diagnosis information provided by the medical staff end, and when an ordinary user is diagnosed with hypertension, convert it into a patient user and store the diagnosis information in the user database. The patient user management unit determines the clinical blood pressure level of the patient based on the user-end blood pressure data and the hypertension diagnosis information, including normal high-value blood pressure, mild hypertension, and moderate-severe hypertension levels. If the patient is determined to have moderate-severe hypertension, the system will push a medication warning message to the patient. The patient management unit intelligently pushes corresponding health suggestions according to the patient's clinical blood pressure level and cardiovascular risk information: when the patient's blood pressure level is normal high-value and the risk is low or medium-risk, or the blood pressure is mildly high and the risk is low, a blood pressure lowering lifestyle intervention suggestion is pushed; if the patient's blood pressure is normal high-value and the risk is high or very high, a medication suggestion is pushed; if the blood pressure is mildly high and the risk is medium, high, or very high, a medication warning message is pushed.

[0225] It can be seen from this that the blood pressure management system provided by the embodiments of the present application can effectively convert ordinary users into patient users, timely obtain and analyze hypertension diagnosis information, thereby accurately judging the clinical blood pressure level of patients, and providing medication warnings when necessary. Through the intelligent push of lifestyle interventions and medication suggestions, it helps to reduce the risk of cardiovascular diseases and improve the overall blood pressure health management effect.

[0226] In an optional embodiment, the user management module further includes a surgical user management unit; the surgical user management unit is configured to manage patient users as patients with poor drug control or patients who cannot use drugs.

[0227] In an optional embodiment, the surgical user management unit is further configured to: identify the tissue morphology and tissue size of the target tissue of the surgical user according to the preoperative image data; determine the standard blood pressure level of the surgical user according to the preoperative quantitative data; according to the tissue morphology, tissue size, standard blood pressure level, basic patient information of the surgical user, and the historical ablation surgery planning scheme, push to the user side and the medical staff side a surgical planning suggestion including the planned ablation position, planned ablation points, planned ablation time, and planned surgery duration of the surgical user; and monitor at least one blood pressure data of the surgical user after the ablation surgery is performed, and push postoperative recovery suggestions to the patient user.

[0228] In the above implementation process, the surgical user management unit is responsible for managing patients with poor drug control or patients who cannot use drugs. The surgical user management unit obtains the morphology and size of the target tissue by identifying the preoperative image data, and determines the standard blood pressure level according to the preoperative quantitative data. Combining the basic information of the patient and the historical surgical plan, it pushes detailed surgical planning suggestions to the user side and the medical staff side, including the planned ablation position, points, time, and duration. In addition, the system also monitors the blood pressure data after the surgery and pushes postoperative recovery suggestions to the patient.

[0229] It can be seen from this that the blood pressure management system provided by the present application provides personalized surgical planning and postoperative tracking for surgical users, optimizes the treatment process of hypertensive patients, and improves the treatment effect and the rehabilitation experience of patients.

[0230] In an optional embodiment, the blood pressure health management system provided by the present application shares at least part of the target user data with a third-party platform.

[0231] Among them, for a third-party platform, such as a hospital platform, by connecting to the existing hospital platform, the blood pressure health management system of the present application can achieve data interconnection, promote information sharing and collaborative management. Exemplarily, the blood pressure health management system provided by the present application can interact in real time with the hospital's electronic health record (EHR) or other medical information systems to ensure that the blood pressure monitoring data, diagnosis information, and treatment records of users can be accessed by medical staff in a timely manner; on the other hand, by integrating the data of the hospital platform, the blood pressure health management system provided by the embodiments of the present application can more comprehensively analyze the health trends of patients and provide strong support for prevention and intervention.

[0232] The present application provides a health management device, which includes a processor and a memory. Among them, computer program instructions suitable for execution by the processor are stored in the memory. When the computer program instructions are run by the processor, the processor is caused to execute the following methods: obtaining at least one blood pressure data of a target user from a target user database; wherein the blood pressure data includes blood pressure data monitored by at least one blood pressure monitoring device associated with the target user; and managing the target user and generating a blood pressure health management recommendation for the target user based on at least the at least one blood pressure data.

[0233] Please refer to Figure 11 , Figure 11 which is a schematic structural diagram of an electronic device provided by an embodiment of the present application. An electronic device 200 provided by an embodiment of the present application includes: a processor 201 and a memory 202. The memory 202 stores machine-readable instructions executable by the processor 201. When the machine-readable instructions are executed by the processor 201, the above-mentioned blood pressure health management method is executed.

[0234] Based on the same inventive concept, an embodiment of the present application further provides a computer-readable storage medium. Computer program instructions are stored in the computer-readable storage medium. When the computer program instructions are read and run by a processor, the steps in any implementation manner of the above-mentioned blood pressure health management method are executed.

[0235] The computer-readable storage medium may be various media that can store program codes, such as a random access memory (RAM), a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), etc.

[0236] In this text, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variation thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising..." does not exclude the presence of additional identical elements in the process, method, article or device comprising the said element.

[0237] The above description is only for the embodiments of the present application and is not intended to limit the protection scope of the present application. For those skilled in the art, the present application may have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the protection scope of the present application.

Claims

1. A blood pressure health management method, characterized in that, The blood pressure health management method is applied to multiple target users associated with at least one blood pressure monitoring device; The blood pressure health management method includes: Obtaining at least one piece of blood pressure data of a target user from a target user database; wherein, the blood pressure data includes the blood pressure data monitored by the blood pressure monitoring device; Managing the target user based on at least the at least one piece of blood pressure data, and generating a blood pressure health management recommendation for the target user; wherein, the blood pressure health management recommendation includes an ablation surgery recommendation.

2. The blood pressure health management method according to claim 1, wherein Wherein, The blood pressure monitoring device includes an autonomous blood pressure monitoring device; the blood pressure data includes the user-end blood pressure data corresponding to the autonomous blood pressure monitoring device; the target user includes an ordinary user; The managing the target user based on at least the at least one piece of blood pressure data, and generating a blood pressure health management recommendation for the target user, includes: Managing the ordinary user according to at least one piece of the user-end blood pressure data, and generating a blood pressure health management recommendation that is operable by the ordinary user.

3. The blood pressure health management method according to claim 2, wherein, The managing the ordinary user according to at least one piece of the user-end blood pressure data, and generating a blood pressure health management recommendation that is operable by the ordinary user, includes: Determining at least according to at least one piece of the user-end blood pressure data the blood pressure reference level of the ordinary user; wherein, the blood pressure reference level includes an ideal blood pressure level, a borderline hypertension blood pressure level, and a hypertension warning blood pressure level; If it is determined that the blood pressure reference level of the ordinary user is the ideal blood pressure level, then pushing hypertension publicity information to the ordinary user; If it is determined that the blood pressure reference level of the ordinary user is the borderline hypertension blood pressure level, then pushing blood pressure-lowering lifestyle intervention suggestions and medical treatment suggestions to the ordinary user; If it is determined that the blood pressure reference level of the ordinary user is the hypertension warning blood pressure level, then pushing a medical treatment warning information to the target user.

4. The blood pressure health management method according to claim 2, characterized in that, Wherein, The target user further includes a patient user; the blood pressure data further includes hypertension diagnosis information; the managing the ordinary user according to at least one piece of the user-end blood pressure data further includes: Determining the ordinary user as a patient user according to the user-end blood pressure data and the hypertension diagnosis information.

5. The blood pressure health management method according to claim 4, characterized in that The managing the target user based on at least the at least one piece of blood pressure data, and generating a blood pressure health management recommendation for the target user, further includes: Pushing a medical intervention suggestion to the patient user according to the blood pressure data.

6. The blood pressure health management method according to claim 5, wherein, The pushing a medical intervention suggestion to the patient user according to the blood pressure data, includes: Determining at least according to the user-end blood pressure data and the hypertension diagnosis information the clinical blood pressure level of the patient user; wherein, the clinical blood pressure level includes a moderate to severe hypertension level; If it is determined that the clinical blood pressure level of the patient user is the moderate to severe hypertension level, then pushing a medication warning information to the patient user.

7. The blood pressure health management method according to claim 5, wherein Wherein, The blood pressure data further includes cardiovascular diagnosis information; the clinical blood pressure level further includes a normal high value blood pressure level and a mild hypertension level; the pushing a medical intervention suggestion to the patient user according to the blood pressure data further includes: If it is determined that the clinical blood pressure level of the patient user is in the normal high value blood pressure level or the mild hypertension level, generate blood pressure health management suggestions for the patient user according to the cardiovascular diagnosis information of the patient user; In the case where the clinical blood pressure level of the patient user is in the normal high value blood pressure level and the cardiovascular diagnosis information is low-risk or medium-risk; or, in the case where the clinical blood pressure level of the patient user is in the mild hypertension level and the cardiovascular diagnosis information is low-risk, generate lifestyle intervention suggestions for blood pressure reduction; In the case where the cardiovascular diagnosis information of the patient user is in the normal high value blood pressure level and the cardiovascular diagnosis information is high-risk or very high-risk, generate medication suggestions; In the case where the cardiovascular diagnosis information of the patient user is in the mild hypertension level and the cardiovascular diagnosis information is medium-risk or high-risk or very high-risk, generate medication warning information.

8. The blood pressure health management method according to claim 7, characterized in that, The blood pressure health management method further includes: After generating the medication warning information or the medication suggestions, judge whether the patient user is a patient with poor drug control according to the blood pressure data of the patient user corresponding to the generated medication warning information or the medication suggestions within a preset time period; And, in the case of generating the medication warning information or the medication suggestions, judge whether the corresponding patient user is a patient who cannot use drugs; If the patient user is a patient with poor drug control or a patient who cannot use drugs, generate ablation surgery suggestions; After confirming that the patient user will undergo the ablation surgery through the preoperative planning plan, determine the patient user as a surgical user and generate surgical planning suggestions for the surgical user.

9. The blood pressure health management method according to claim 8, wherein The generation of the surgical planning suggestions for the surgical user includes: According to the preoperative image data, identify the tissue morphology and tissue size of the target tissue of the surgical user; Generate a patient information report according to the basic patient information of the surgical user; Determine the standard blood pressure level of the surgical user according to the preoperative quantitative data; Determine the planned ablation location, planned ablation points, planned ablation time and planned surgical duration of the surgical user according to the tissue morphology, tissue size, standard blood pressure level, the patient information report and the historical ablation surgery planning plan.

10. The blood pressure health management method according to claim 9, characterized in that, The generation of the patient information report according to the basic patient information of the surgical user includes: Obtain the basic patient information of the surgical user; where the basic patient information includes height, weight, genetic history and / or allergy history; Perform data preprocessing on the basic patient information; Extract the patient information features of the preprocessed basic patient information and obtain the patient information report based on the target neural network model.

11. The blood pressure health management method according to claim 9, wherein The determination of the standard blood pressure level of the surgical user according to the preoperative quantitative data includes: Obtain the preoperative quantitative data; where the preoperative quantitative data includes blood pressure, heart rate and / or blood sugar for 24 hours; Perform data preprocessing on the preoperative quantitative data; Extract the level features of the preprocessed preoperative quantitative data and perform training and evaluation based on a preset machine model to generate the standard blood pressure level.

12. The blood pressure health management method according to claim 9, wherein, The described blood pressure health management method further includes: Monitoring at least one blood pressure data of the surgical user after ablation surgery is performed, and pushing postoperative recovery suggestions to the patient user.

13. A blood pressure health management system, characterized in that, The described blood pressure health management system includes a device management module, a user management module, and a user database; The device management module is configured to bind a blood pressure monitoring device associated with a target user, obtain blood pressure data measured by the blood pressure monitoring device, and store it in the user database; The user management module is configured to manage the target user based on at least one piece of the at least one blood pressure data of the target user, and push blood pressure health management suggestions to the user terminal.

14. The blood pressure health management system according to claim 13, wherein The blood pressure monitoring device includes an autonomous blood pressure monitoring device, the blood pressure data includes user terminal blood pressure data corresponding to the autonomous blood pressure monitoring device, and the target user includes an ordinary user; the user management module includes an ordinary user management unit, and the ordinary user management unit is configured to: Determine the blood pressure reference level of the ordinary user based on at least one piece of the user terminal blood pressure data, and store the blood pressure reference level in the user database; wherein, the blood pressure reference level includes an ideal blood pressure level, a borderline hypertension blood pressure level, and a hypertension warning blood pressure level; If it is determined that the blood pressure reference level of the ordinary user is the ideal blood pressure level, push hypertension publicity information to the user terminal; If it is determined that the blood pressure reference level of the ordinary user is the borderline hypertension blood pressure level, push blood pressure-lowering lifestyle intervention suggestions and medical advice to the user terminal; If it is determined that the blood pressure reference level of the ordinary user is the hypertension warning blood pressure level, push medical warning information to the user terminal.

15. The blood pressure health management system according to claim 14, characterized in that, The target user further includes a patient user; the user management module further includes a patient user management unit; The user management module is further configured to obtain blood pressure data including the hypertension diagnosis information of the target user from the medical staff terminal, and in the case where the target user is an ordinary user, convert the ordinary user into a patient user and store the hypertension diagnosis information in the user database; The patient user management unit is configured to determine the clinical blood pressure level of the patient user based on the user terminal blood pressure data and the hypertension diagnosis information; wherein, the clinical blood pressure level includes normal high-value blood pressure, mild hypertension level, and moderate-severe hypertension level; and If it is determined that the clinical blood pressure level of the patient user is the moderate-severe hypertension level, push medication warning information to the user terminal.

16. The blood pressure health management system according to claim 15, wherein The user management module is further configured to obtain cardiovascular diagnosis information of the patient user from the medical staff terminal and store the cardiovascular diagnosis information in the user database; The patient management unit is further configured to, in the case where the clinical blood pressure level of the patient user is the normal high-value blood pressure level and the cardiovascular diagnosis information is low-risk or medium-risk; or, the clinical blood pressure level of the patient user is the mild hypertension level and the cardiovascular diagnosis information is low-risk; push blood pressure-lowering lifestyle intervention suggestions to the user terminal; When the cardiovascular diagnosis information of the patient user is at the normal high blood pressure level and the cardiovascular diagnosis information is at high risk or very high risk, push medication advice to the user terminal; When the cardiovascular diagnosis information of the patient user is at the mild hypertension level and the cardiovascular diagnosis information is at medium risk, high risk or very high risk, push medication warning information to the user terminal.

17. The blood pressure health management system according to claim 15, characterized in that, The user management module further includes a surgical user management unit; The surgical user management unit is configured to manage the patient user as a patient with poor drug control or a patient who cannot use drugs.

18. The blood pressure health management system according to claim 17, wherein The surgical user management unit is further configured to: Identify the tissue morphology and tissue size of the target tissue of the surgical user according to the preoperative image data; Determine the standard blood pressure level of the surgical user according to the preoperative quantitative data; Push surgical planning advice including the planned ablation position, planned ablation points, planned ablation time and planned operation duration of the surgical user to the user terminal and the medical staff terminal according to the tissue morphology, tissue size, standard blood pressure level, basic patient information of the surgical user and the historical ablation operation planning scheme; And Monitor at least one blood pressure data of the surgical user after the ablation operation and push postoperative recovery advice to the patient user.

19. The blood pressure health management system according to claim 13, wherein The blood pressure health management system shares at least part of the target user data with a third-party platform.

20. A health management device, comprising: A processor and a memory, wherein the memory stores computer program instructions suitable for execution by the processor, and when the computer program instructions are run by the processor, the processor is caused to execute the following methods including: Obtain at least one blood pressure data of a target user in the target user database; wherein the blood pressure data includes blood pressure data monitored by at least one blood pressure monitoring device associated with the target user; Manage the target user at least based on the at least one blood pressure data and generate blood pressure health management advice for the target user.

21. A computer-readable storage medium, characterized in that, Computer program instructions are stored in the computer-readable storage medium, and when the computer program instructions are run by a processor, the steps in the method according to any one of claims 1-12 are executed.

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