Intelligent diagnosis and treatment auxiliary system for cardiovascular diseases

Abstract

The invention discloses a cardiovascular disease intelligent diagnosis and treatment auxiliary system which comprises a hospital server terminal, a cardiovascular disease intelligent diagnosis and treatment cloud platform, a doctor mobile terminal, a medical care mobile terminal and a patient mobile terminal. The hospital server terminal is used for compiling a clinical patient medical record created and uploaded by a doctor and data uploaded by medical care for clinical examination of a patient, and creating a medical record model of the patient, and the hospital server terminal uploads the created medical record model to the cardiovascular disease intelligent diagnosis and treatment cloud platform for cardiovascular case big data collection; according to the intelligent diagnosis and treatment auxiliary system for the cardiovascular disease, in the intelligent diagnosis and treatment process, a medical record model of a patient can be analyzed, healing duration data of cardiovascular diseases of the same type in a patient healing and disease death record storage unit are retrieved and called, and the healing duration of the patient is calculated and predicted through big data; and the disease death duration data of the same type of cardiovascular diseases in the patient healing disease death record storage unit are retrieved and called, and the survival rate of the patient is calculated and predicted through big data.

Description

Technical Field

[0001] The present invention relates to the technical field of cardiovascular disease diagnosis and treatment, and specifically to an intelligent cardiovascular disease diagnosis and treatment auxiliary system. Background Art

[0002] Cardiovascular disease is a type of disease involving the heart and blood vessels, mainly including the following common types: coronary heart disease, hypertension, arrhythmia, heart failure. Cardiovascular health care covers multiple aspects of diagnosis, treatment and rehabilitation. Through the comprehensive use of various medical methods, cardiovascular diseases can be effectively prevented and treated, and the quality of life and survival rate of patients can be improved. Patent: CN 117116490A discloses a method for constructing a cardiovascular disease assessment model, dietary therapy and health management system. The construction method includes: S1: preparing a data set; S2: feature screening; S3: model construction: using the proportional risk regression method to fit the training set to construct a cardiovascular disease assessment model; S4: model optimization: optimizing the parameters of the cardiovascular disease assessment model through the logarithmic loss function combined with the gradient descent algorithm; S5: model evaluation and verification; S6: model application.

[0003] In the existing market, the diagnosis and treatment of cardiovascular diseases are carried out by doctors in hospitals. Big data analysis and intelligent diagnosis and treatment have not been widely used in cardiovascular disease treatment. Using big data intelligent analysis technology to solve the clinical diagnosis in the field of cardiovascular diseases is a difficulty that existing technologies have to overcome. The existing hospital system does not have the ability to collect big data on cardiovascular cases and treatment methods in various hospitals. The existing hospital system does not have the ability to analyze, self-check and provide early warning prompts for clinical patients' medical records. The existing hospital system does not have the ability to predict big data on clinical patients' cure rate and survival rate. Medical staff and patients' families in the existing hospital system cannot remotely obtain and browse clinical patients' medical records and examination data through mobile terminals. Therefore, it is very meaningful to propose a smart diagnosis and treatment auxiliary system for cardiovascular disease based on the above. Summary of the invention

[0004] The purpose of the present invention is to provide an intelligent cardiovascular disease diagnosis and treatment auxiliary system to solve the problems raised in the above-mentioned background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: including a hospital server terminal, a cardiovascular disease intelligent diagnosis and treatment cloud platform, a doctor's mobile terminal, a medical mobile terminal and a patient's mobile terminal;

[0006] The hospital server terminal includes a medical record model building module, which is used to compile the clinical patient medical records created and uploaded by doctors and the data uploaded by medical staff on the clinical examination of patients, and create the patient's medical record model. Each hospital server terminal uploads the created medical record model to the cardiovascular disease smart diagnosis and treatment cloud platform to collect cardiovascular case big data;

[0007] The doctor's mobile terminal includes a medical record establishment module, which is used by doctors to establish medical records of clinical patients. Doctors can use the doctor's mobile terminal to obtain and browse cardiovascular cases in the cardiovascular disease smart diagnosis and treatment cloud platform;

[0008] The medical mobile terminal includes an electrocardiogram data acquisition unit, an echocardiogram acquisition unit, a blood test data acquisition unit, a cardiac magnetic resonance imaging acquisition unit, and a cardiovascular angiography acquisition unit, and is used by medical workers to upload clinical patient symptom data acquired through medical testing instruments. Symptom data includes: electrocardiogram data, echocardiogram data, blood test data, cardiac magnetic resonance imaging data, and cardiovascular angiography data;

[0009] Patient mobile terminals are used by patients and their families to obtain real-time health status and disease data;

[0010] The cardiovascular health monitoring and early warning cloud server includes a patient data modeling and recording module, a cardiovascular health analysis and detection early warning module, a cardiovascular patient treatment feedback module, a database and a patient survival rate prediction module;

[0011] The patient data modeling and recording module includes a patient data uploading and collecting unit and a patient cardiovascular image modeling unit, which are used to obtain the data of the medical record model uploaded by the mobile terminal and manage the data of the medical record model. The patient cardiovascular image modeling unit processes the collected patient examination data and constructs an image model.

[0012] The cardiovascular health analysis, detection and early warning module is used to analyze the acquired patient medical record data and examination data, determine whether the patient's cardiovascular health is healthy, collect cardiovascular abnormality data and issue early warnings;

[0013] The cardiovascular disease treatment feedback module is used to analyze the cardiovascular abnormality data and retrieve treatments for the same type of cardiovascular abnormalities in the database;

[0014] The database includes a medical record model storage module, a treatment means storage unit, a normal cardiovascular health big data storage unit, a healthy cardiovascular image model storage unit and a patient cure and death record storage unit, which are used to store the medical record model data and the treatment means corresponding to the medical records, and store the normal cardiovascular big data of healthy people, and record and store the duration of patient cure and death in the medical record model data.

[0015] The patient survival rate prediction module is used to analyze the data of the cardiovascular disease, retrieve and call the cured and fatal data of the same type of cardiovascular disease in the database, and predict the patient's survival rate through big data calculation.

[0016] According to the above technical solution, the doctor's mobile terminal includes a patient basic information entry module, a patient pathological characteristics acquisition module, a treatment method entry module and a medication information entry module, which are used by doctors to create medical records of clinical patients and enter patient basic information, pathological characteristics, treatment methods and medication information.

[0017] According to the above technical solution, the medical mobile terminal includes an electrocardiogram data acquisition unit, an echocardiogram data acquisition unit, a blood test data acquisition unit, a cardiac magnetic resonance imaging acquisition unit and a cardiovascular angiography acquisition unit, which are used by medical staff to collect and obtain electrocardiogram data, echocardiogram data, blood test data, cardiac magnetic resonance imaging data and cardiovascular angiography data of clinical patients.

[0018] According to the above technical solution, the cardiovascular health analysis detection and early warning module also includes a patient data proofreading and analysis unit, a cardiovascular image model proofreading and analysis unit, an abnormal data recording unit and an abnormal alarm unit;

[0019] The patient data proofreading and analyzing unit is used to obtain and analyze the patient's medical history data and examination data, so as to proofread and analyze the patient's examination data and the normal cardiovascular big data of healthy people to determine whether the patient's cardiovascular system is healthy;

[0020] The cardiovascular image model proofreading and analysis unit is used to obtain an image model constructed by analyzing patient examination data, call a healthy cardiovascular image model in a database, and perform proofreading and analysis with the image model constructed by the patient examination data, so as to analyze and detect the patient's cardiovascular pathological characteristics;

[0021] The abnormal data recording unit is used to record and store the patient's abnormal cardiovascular data analyzed above;

[0022] The abnormality alarm unit is used to send a warning signal to the mobile terminal when the patient's cardiovascular abnormality is analyzed, and the mobile terminal receives the warning signal and issues a clinical alarm.

[0023] According to the above technical solution, the cardiovascular patient treatment means feedback module includes a historical treatment means calling unit for similar patients and a clinical treatment means uploading record unit;

[0024] The historical treatment method calling unit for similar patients is used to retrieve and call the treatment methods for the same type of cardiovascular abnormalities in the database through the cardiovascular abnormality data, and send the called treatment methods for the same type of cardiovascular abnormalities to the mobile terminal for display, so as to assist clinical cardiovascular disease treatment;

[0025] The clinical treatment means uploading record unit is used to upload and record the clinical treatment means and medication records of the patient's cardiovascular abnormalities used by medical staff.

[0026] According to the above technical solution, the patient survival rate prediction module includes a patient cure time recording module, a patient death time recording module, a large data analysis unit for the treatment time of similar patients, and a large data analysis unit for the survival rate of similar patients;

[0027] The patient recovery time recording module is used to analyze the patient medical record model data and record the patient recovery time, and the patient recovery time data is stored in the patient recovery and death record storage unit in the database;

[0028] The patient death time recording module is used to analyze the patient medical record model data and record the patient death time. The patient death time data is stored in the patient cure and death record storage unit in the database.

[0029] The treatment time data analysis unit for patients of the same type is used to retrieve and call the data on the cure time of the same type of cardiovascular disease in the patient cure and death record storage unit through the patient's cardiovascular disease data, and predict the patient's cure time through big data calculation;

[0030] The big data analysis unit for the survival rate of patients of the same type is used to retrieve and call the death time data of the same type of cardiovascular diseases in the patient cure and death record storage unit through the patient's cardiovascular disease data, and predict the patient's survival rate through big data calculation.

[0031] According to the above technical solution, the doctor's mobile terminal, the medical mobile terminal and the patient's mobile terminal are all provided with a patient clinical medical record data calling module, a module for obtaining treatment methods for the same type of disease, an early warning prompt module and a display module;

[0032] The patient clinical medical record data calling module is used for doctors, medical staff and patient family members to obtain the patient medical records in the hospital server terminal through mobile terminals;

[0033] The module for acquiring treatment methods for the same type of diseases is used by doctors and medical workers to acquire big data of treatment methods for the same type of diseases in the intelligent cardiovascular disease diagnosis and treatment cloud platform;

[0034] The early warning prompt module is used to provide early warning prompts when cardiovascular abnormalities occur to the doctor's mobile terminal, the medical mobile terminal and the patient's mobile terminal;

[0035] The display module is used for the doctor's mobile terminal, the medical staff's mobile terminal and the patient's mobile terminal to obtain and display medical record data and treatment methods.

[0036] According to the above technical solution, an interdisciplinary consultation platform module is also included. The interdisciplinary consultation platform module is arranged inside the hospital server terminal, and the interdisciplinary consultation platform module includes the following units:

[0037] Multidisciplinary expert invitation unit: A combination of content-based recommendation algorithms and collaborative filtering algorithms is used to match patients’ medical records (such as symptoms and test results) with the experts’ professional fields. For example, if a patient has arrhythmia, experts who are good at cardiac electrophysiology will be recommended first.

[0038] Calculation process: The patient's medical record data is represented as a feature vector p = (p1, p2, ..., p n ), where each p i represents a specific symptom and examination result, and the expert's professional field is also represented as a feature vector e = (e1, e2, ..., e m ), the degree of matching is determined by calculating the cosine similarity,

[0039] Recommend expert doctors based on historical consultation records. For example, if a certain expert has a high success rate in treating similar conditions, he will be recommended first. Calculation process: Construct the user-item matrix R, where R ij Represents the evaluation of the i-th patient on the j-th expert. Use matrix decomposition method to predict unknown scores: R≈PQ T , where P and Q are low-dimensional representations of users and items respectively;

[0040] Video conferencing unit: provides high-definition video conferencing function, supporting multi-party real-time communication and discussion;

[0041] File sharing and collaboration unit: allows participants to upload, view and edit relevant medical documents, such as medical records and imaging materials;

[0042] Case discussion record unit: records the discussion content, diagnosis opinions and final treatment plan during the consultation process;

[0043] Notification and reminder unit: Send consultation invitations and time change notifications to doctors participating in the consultation, and remind them before the consultation begins.

[0044] The interdisciplinary consultation platform module also includes:

[0045] Intelligent matching unit: Using big data analysis technology, recommend a team of experts to participate in the consultation based on the patient's specific situation and historical data; using random forest or gradient boosting tree ensemble learning algorithms to extract the patient's age, gender, medical history, examination result characteristics, as well as the expert's professional background and historical consultation effect characteristics, use historical data to train the model, optimize hyperparameters through cross-validation, input new patient data, and the model outputs the most suitable expert list and confidence score

[0046] Permission management unit: ensure that only authorized users can access specific medical information, and protect data security and privacy; define the relationship between roles, permissions, and users, dynamically assign permissions based on user roles, and ensure that only authorized users can access specific resources

[0047] Remote Operation Guidance Unit: Provides doctors in remote areas with operation guidance for remote surgery and complex examinations, and realizes an intuitive teaching experience through AR / VR technology.

[0048] The interdisciplinary consultation platform module also includes:

[0049] Decision support system unit: Integrates the latest medical guidelines, clinical trial results, and big data analysis to provide a scientific basis for decision-making during the consultation process; extracts key information from the literature through natural language processing (NLP) technology, and combines it with the patient's specific data to generate personalized treatment recommendations;

[0050] Follow-up plan generation unit: automatically generates follow-up confirmation plans based on consultation results and synchronizes them to the doctor's mobile terminal, medical mobile terminal and patient mobile terminal to ensure continuous tracking of the patient's recovery; the follow-up plan includes regular check-ups, medication adjustments and lifestyle recommendations, and sets reminder functions;

[0051] Knowledge base update unit: regularly update the medical knowledge base within the consultation platform, including the latest research progress and treatment methods, to maintain the professionalism and timeliness of the platform; automatically capture and integrate the latest research results by subscribing to authoritative medical journals and databases for reference during consultation;

[0052] Quality Assessment and Feedback Unit: Collect feedback after consultation, evaluate the consultation process and service quality, and continuously improve the consultation process and service level through questionnaire surveys and data analysis.

[0053] Compared with the prior art, the present invention has the following beneficial effects:

[0054] 1. The intelligent cardiovascular disease diagnosis and treatment auxiliary system creates clinical patient medical records and collects clinical examination data of patients through mobile terminals of doctors and medical staff. It builds medical record models with the created medical records and collected examination data and uploads them to the hospital server terminal, realizing the collection of big data of cardiovascular health medical records and big data of cardiovascular cases in various hospitals. Medical staff, patients and their families can remotely obtain patient medical records and test symptoms through mobile terminals, which improves the acquisition and browsing of cardiovascular disease diagnosis and treatment data. Doctors can obtain and browse cardiovascular cases and corresponding treatment methods in the intelligent cardiovascular disease diagnosis and treatment cloud platform through mobile terminals, creating a cardiovascular disease intelligent data platform for doctors to continue learning;

[0055] 2. The intelligent cardiovascular disease diagnosis and treatment auxiliary system obtains patient examination data through the patient data proofreading and analysis unit in the intelligent cardiovascular disease diagnosis and treatment cloud platform, and proofreads and analyzes it with the normal cardiovascular big data of healthy people to determine whether the patient's cardiovascular is healthy. The cardiovascular image model proofreading and analysis unit calls the healthy cardiovascular image model in the database, and proofreads and analyzes it with the image model constructed with the patient's examination data, and analyzes and detects the patient's cardiovascular pathological characteristics. The abnormal data recording unit stores the above-analyzed abnormal cardiovascular data of the patient. When the abnormal alarm unit analyzes the patient's cardiovascular abnormality, it sends a warning signal to the doctor's mobile terminal, the medical mobile terminal and the patient's mobile terminal. The doctor's mobile terminal, the medical mobile terminal and the patient's mobile terminal receive the warning signal and issue a clinical alarm to the corresponding patient's medical staff and the patient's family members;

[0056] 3. During the intelligent diagnosis and treatment process, the intelligent cardiovascular disease diagnosis and treatment cloud system can analyze the patient's medical record model, retrieve and call the data on the duration of cure of the same type of cardiovascular disease in the patient's cure and death record storage unit, and predict the patient's cure time through big data calculation; retrieve and call the data on the duration of death of the same type of cardiovascular disease in the patient's cure and death record storage unit, and predict the patient's survival rate through big data calculation;

[0057] 4. The historical treatment method calling unit for similar patients in the cardiovascular disease intelligent diagnosis and treatment cloud system searches and calls the treatment methods for the same type of cardiovascular abnormalities in the database through cardiovascular abnormality data, and sends the called treatment methods for the same type of cardiovascular abnormalities to the mobile terminal for display, assisting clinical cardiovascular disease treatment. The clinical treatment method uploading record unit uploads the clinical treatment methods and medication records of the patients' cardiovascular abnormalities by medical staff, playing the role of clinical medical cardiovascular health auxiliary treatment;

[0058] 5. Through the collaborative work of multidisciplinary experts, professional knowledge in different fields can be integrated to more comprehensively assess the patient's condition and develop more accurate and personalized treatment plans. The multidisciplinary expert invitation unit and intelligent matching unit can efficiently dispatch medical resources and avoid waste of resources due to information asymmetry. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0060] Figure 1 It is a system flow chart of the intelligent diagnosis and treatment auxiliary system for cardiovascular disease of the present invention;

[0061] Figure 2 It is a structural schematic diagram of a mobile terminal of the intelligent cardiovascular disease diagnosis and treatment auxiliary system of the present invention;

[0062] In the figure: 1. Hospital server terminal; 2. Intelligent cardiovascular disease diagnosis and treatment cloud platform; 3. Doctor mobile terminal; 4. Medical mobile terminal; 5. Patient mobile terminal; 6. Patient clinical medical record data call module; 7. Same type of disease treatment method acquisition module; 8. Early warning prompt module; 9. Display module;

[0063] 11. Medical record modeling module; 21. Patient data modeling and recording module; 22. Cardiovascular health analysis, detection and early warning module; 23. Cardiovascular patient treatment feedback module; 24. Database; 25. Patient survival rate prediction module;

[0064] 211. Patient data uploading and collecting unit; 212. Patient cardiovascular image modeling unit;

[0065] 221. Patient data proofreading and analyzing unit; 222. Cardiovascular image model proofreading and analyzing unit; 223. Abnormal data recording unit; 224. Abnormal alarm unit;

[0066] 231. Unit for calling historical treatment methods for patients with similar diseases; 232. Unit for uploading records of clinical treatment methods;

[0067] 241. Medical record model storage module; 242. Treatment means storage unit; 243. Normal cardiovascular health big data storage unit; 244. Healthy cardiovascular image model storage unit; 245. Patient cure and death record storage unit;

[0068] 251. Patient recovery time recording module; 252. Patient death time recording module; 253. Big data analysis unit for treatment time of similar patients; 254. Big data analysis unit for survival rate of similar patients;

[0069] 26. Interdisciplinary consultation platform module. DETAILED DESCRIPTION

[0070] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0071] See also Figures 1 to 2 , the present invention provides a technical solution: a cardiovascular disease intelligent diagnosis and treatment auxiliary system, a cardiovascular disease intelligent diagnosis and treatment auxiliary system, comprising a hospital server terminal 1, a cardiovascular disease intelligent diagnosis and treatment cloud platform 2, a doctor's mobile terminal 3, a medical mobile terminal 4 and a patient mobile terminal 5;

[0072] The hospital server terminal 1 includes a medical record model building module 11, which is used to compile the clinical patient medical records created and uploaded by doctors and the data uploaded by medical staff on the clinical examination of patients, and create the patient's medical record model. Each hospital server terminal 1 uploads the created medical record model to the cardiovascular disease intelligent diagnosis and treatment cloud platform 2 to collect cardiovascular case big data;

[0073] The doctor's mobile terminal 3 includes a medical record establishment module 31, which is used by doctors to establish medical records of clinical patients. Doctors can obtain and browse cardiovascular cases in the cardiovascular disease intelligent diagnosis and treatment cloud platform 2 through the doctor's mobile terminal 3;

[0074] The medical mobile terminal 4 includes an electrocardiogram data acquisition unit 41, an echocardiogram acquisition unit 42, a blood test data acquisition unit 43, a cardiac magnetic resonance imaging acquisition unit 44, and a cardiovascular angiography acquisition unit 45, which are used by medical workers to upload clinical patient symptom data acquired through medical testing instruments, and the symptom data include: electrocardiogram data, echocardiogram data, blood test data, cardiac magnetic resonance imaging data, and cardiovascular angiography data;

[0075] Patient mobile terminal 5, used for patients and their family members to obtain health status and symptom data in real time;

[0076] The cardiovascular disease intelligent diagnosis and treatment cloud platform 2 includes a patient data modeling and recording module 21, a cardiovascular health analysis and detection early warning module 22, a cardiovascular patient treatment feedback module 23, a database 24 and a patient survival rate prediction module 25;

[0077] The patient data modeling and recording module 21 includes a patient data uploading and collecting unit 211 and a patient cardiovascular image modeling unit 212, which are used to obtain the data of the medical record model uploaded by the mobile terminal and manage the data of the medical record model. The patient cardiovascular image modeling unit 212 processes the collected patient examination data and constructs an image model.

[0078] The cardiovascular health analysis, detection and early warning module 22 is used to analyze the acquired patient medical records and examination data, determine whether the patient's cardiovascular health is good, collect cardiovascular abnormality data and issue early warnings;

[0079] The cardiovascular patient treatment method feedback module 23 is used to analyze cardiovascular abnormality data and retrieve treatment methods for the same type of cardiovascular abnormality in the database 24;

[0080] The database 24 includes a medical record model storage module 241, a treatment means storage unit 242, a normal cardiovascular health big data storage unit 243, a healthy cardiovascular image model storage unit 244 and a patient cure and death record storage unit 245, which are used to store medical record model data and the corresponding medical record treatment means, and store normal cardiovascular big data of healthy people, and record the length of time it takes for patients to be cured and die in the medical record model data.

[0081] The patient survival rate prediction module 25 is used to analyze the data of cardiovascular diseases, retrieve and call the cured and deceased data of the same type of cardiovascular diseases in the database 24, and predict the patient's survival rate through big data calculation.

[0082] It should be noted that the medical records of clinical patients are created and the clinical examination data of patients are collected through the doctor's mobile terminal 3 and the medical staff's mobile terminal 4. The created medical records and the collected examination data are used to establish a medical record model and uploaded to the hospital server terminal 1, so as to realize the collection of big data of cardiovascular health medical records and the collection of big data of cardiovascular cases in various hospitals. Medical staff, patients and their families can remotely obtain patient medical records and test symptoms through mobile terminals, which improves the acquisition and browsing of cardiovascular disease diagnosis and treatment data. Doctors can obtain and browse cardiovascular cases and corresponding treatment methods in the cardiovascular disease intelligent diagnosis and treatment cloud platform 2 through the doctor's mobile terminal 3, and create a cardiovascular disease intelligent data platform for doctors to continue learning.

[0083] The medical record establishment module 31 includes a patient basic information entry module 311, a patient pathological characteristics acquisition module 312, a treatment method entry module 313 and a medication information entry module 314, which is used by doctors to create medical records for clinical patients and enter patient basic information, pathological characteristics, treatment methods and medication information.

[0084] It should be noted that the doctor establishes a medical record model based on the patient's basic information, medical history, treatment methods, medication information and patient data by establishing a medical record module 31, extracts the patient's pathological characteristics, formulates artificial intelligence algorithm strategies, and builds a neural network model to assist clinical diagnosis and treatment.

[0085] The medical mobile terminal 4 includes an electrocardiogram data acquisition unit 41, an echocardiogram data acquisition unit 42, a blood test data acquisition unit 43, a cardiac magnetic resonance imaging acquisition unit 44 and a cardiovascular angiography acquisition unit 45, which are used by medical staff to acquire the electrocardiogram data, echocardiogram data, blood test data, cardiac magnetic resonance imaging data and cardiovascular angiography data of clinical patients.

[0086] It should be noted that medical workers collect electrocardiogram data, echocardiogram data, blood test data, cardiac magnetic resonance imaging data and cardiovascular angiography data of clinical patients through medical testing instruments.

[0087] The cardiovascular health analysis detection and early warning module 22 also includes a patient data proofreading and analysis unit 221, a cardiovascular image model proofreading and analysis unit 222, an abnormal data recording unit 223 and an abnormal alarm unit 224;

[0088] The patient data proofreading and analyzing unit 221 is used to obtain and analyze the patient's medical history data and examination data, so as to proofread and analyze the patient's examination data and the normal cardiovascular big data of healthy people, and determine whether the patient's cardiovascular system is healthy;

[0089] The cardiovascular image model calibration and analysis unit 222 is used to obtain the image model constructed by analyzing the patient examination data, call the healthy cardiovascular image model in the database 24, and perform calibration and analysis with the image model constructed by the patient examination data, and analyze and detect the patient's cardiovascular pathological characteristics;

[0090] The abnormal data recording unit 223 is used to record and store the patient's abnormal cardiovascular data analyzed above;

[0091] The abnormality alarm unit 224 is used to send a warning signal to the mobile terminal when the patient's cardiovascular abnormality is analyzed. The mobile terminal receives the warning signal and issues a clinical alarm.

[0092] It should be noted that the patient data proofreading and analysis unit 22 in the intelligent cardiovascular diagnosis and treatment cloud platform 2 for cardiovascular disease obtains the patient's examination data, and proofreads and analyzes it with the normal cardiovascular big data of healthy people to determine whether the patient's cardiovascular is healthy. The cardiovascular image model proofreading and analysis unit 222 calls the healthy cardiovascular image model in the database 24, and proofreads and analyzes it with the image model constructed with the patient's examination data, and analyzes and detects the patient's cardiovascular pathological characteristics. The abnormal data recording unit 223 stores the above-analyzed patient cardiovascular abnormality data. When the abnormal alarm unit 224 analyzes the patient's cardiovascular abnormality, it sends a warning signal to the doctor's mobile terminal 3, the medical mobile terminal 4 and the patient's mobile terminal 5. The doctor's mobile terminal 3, the medical mobile terminal 4 and the patient's mobile terminal 5 receive the warning signal and issue a clinical alarm to the corresponding patient's medical staff and the patient's family members.

[0093] The patient survival rate prediction module 25 includes a patient cure time recording module 251, a patient death time recording module 252, a similar patient treatment time big data analysis unit 253 and a similar patient survival rate big data analysis unit 254;

[0094] The patient recovery time recording module 251 is used to analyze the patient medical record model data and record the patient recovery time. The patient recovery time data is stored in the patient recovery and death record storage unit 245 in the database 24;

[0095] The patient death time recording module 252 is used to analyze the patient medical record model data and record the patient death time. The patient death time data is stored in the patient cure and death record storage unit 245 in the database 24.

[0096] The large data analysis unit 253 for the treatment time of patients of the same type is used to retrieve and call the data on the cure time of the same type of cardiovascular diseases in the patient cure and death record storage unit 245 through the patient's cardiovascular disease data, and predict the patient's cure time through big data calculation;

[0097] The big data analysis unit 254 for the survival rate of similar patients is used to retrieve and call the death time data of the same type of cardiovascular diseases in the patient cure and death record storage unit 245 through the patient's cardiovascular disease data, and predict the patient's survival rate through big data calculation.

[0098] It should be noted that the patient recovery time recording module 251 and the patient death time recording module 252 in the cardiovascular disease intelligent diagnosis and treatment cloud platform 2 record the acquired patient medical record data for a long time, record the patient's recovery time, and store the patient's recovery time data in the patient recovery and death record storage unit 245 in the database 24, and record the patient's treatment and death time data, and store the patient's death time data in the patient recovery and death record storage unit 245 in the database 24; the cardiovascular disease intelligent diagnosis and treatment cloud platform 2 can analyze the patient's medical record model during the intelligent diagnosis and treatment process, retrieve and call the recovery time data of the same type of cardiovascular diseases in the patient recovery and death record storage unit 245, and predict the patient's recovery time through big data calculation; retrieve and call the patient recovery and death record storage unit 245 The data of the time to death of the same type of cardiovascular diseases predicts the patient's survival rate through big data calculation.

[0099] The cardiovascular patient treatment means feedback module 23 includes a historical similar patient treatment means calling unit 231 and a clinical treatment means uploading record unit 232;

[0100] The historical treatment method calling unit 231 for similar patients is used to retrieve and call the treatment methods of the same type of cardiovascular abnormalities in the database 24 through cardiovascular abnormality data, and send the called treatment methods of the same type of cardiovascular abnormalities to the clinical data terminal 1 for display, so as to assist clinical cardiovascular disease treatment;

[0101] The clinical treatment means uploading record unit 232 is used to upload and record the clinical treatment means and medication records of the medical staff for the patient's cardiovascular abnormalities.

[0102] It should be noted that the historical treatment means calling unit 231 for similar patients in the cardiovascular disease intelligent diagnosis and treatment cloud platform 2 searches and calls the treatment means for the same type of cardiovascular abnormalities in the database 24 through cardiovascular abnormality data, and sends the called treatment means for the same type of cardiovascular abnormalities to the mobile terminal for display, so as to assist in the clinical treatment of cardiovascular diseases, and uploads the clinical treatment means uploading record unit 232 to record the clinical treatment means and medication records of medical staff for patients' cardiovascular abnormalities.

[0103] The doctor mobile terminal 3, the medical mobile terminal 4 and the patient mobile terminal 5 are all provided with a patient clinical medical record data calling module 6, a module for obtaining treatment methods for the same type of disease 7, an early warning prompt module 8 and a display module 9;

[0104] The patient clinical medical record data calling module 6 is used for doctors, medical staff and patient family members to obtain the patient medical records in the hospital server terminal 1 through a mobile terminal;

[0105] The module 7 for obtaining treatment methods for the same type of diseases is used by doctors and medical workers to obtain big data of treatment methods for the same type of diseases in the intelligent cardiovascular disease diagnosis and treatment cloud platform 2;

[0106] The early warning prompt module 8 is used to provide early warning prompts to the doctor mobile terminal 3, the medical mobile terminal 4 and the patient mobile terminal 5 when cardiovascular abnormalities occur;

[0107] The display module 9 is used by the doctor's mobile terminal 3, the medical mobile terminal 4 and the patient's mobile terminal 5 to obtain and display medical record data and treatment methods.

[0108] It should be noted that the doctor's mobile terminal 3, the medical staff mobile terminal 4 and the patient's mobile terminal 5 remotely obtain the patient's medical records in the hospital server terminal 1 through the patient's clinical medical record data calling module 6, which is convenient for medical staff and patients' families to obtain medical records and patient test data. The doctor's mobile terminal 3, the medical staff mobile terminal 4 and the patient's mobile terminal 5 receive the abnormal diagnosis and treatment warning signal of the cardiovascular disease intelligent diagnosis and treatment cloud platform 2 through the early warning prompt module 8, and the display module 9 obtains and displays medical record data and treatment methods on the mobile terminal.

[0109] The hospital also includes an interdisciplinary consultation platform module 26, which is set on the hospital server terminal 1

[0110] The internal, interdisciplinary consultation platform module 26 includes the following units:

[0111] Multidisciplinary expert invitation unit: Using a combination of content-based recommendation algorithms and collaborative filtering algorithms, the unit analyzes the patient's medical records, such as symptoms and test results, and matches them with the expert's professional field. For example, if a patient has arrhythmia, experts who are good at cardiac electrophysiology will be recommended first;

[0112] Calculation process: The patient's medical record data is represented as a feature vector p = (p1, p2, ..., p n ), where each p i represents a specific symptom and examination result, and the expert's professional field is also represented as a feature vector e = (e1, e2, ..., e m ), the degree of matching is determined by calculating the cosine similarity,

[0113] Recommend expert doctors based on historical consultation records. For example, if a certain expert has a high success rate in treating similar conditions, he will be recommended first. Calculation process: Construct the user-item matrix R, where R ij Represents the evaluation of the i-th patient on the j-th expert. Use matrix decomposition method to predict unknown scores: R≈PQ T , where P and Q are low-dimensional representations of users and items respectively;

[0114] Video conferencing unit: provides high-definition video conferencing function, supporting multi-party real-time communication and discussion;

[0115] File sharing and collaboration unit: allows participants to upload, view and edit relevant medical documents, such as medical records and imaging materials;

[0116] Case discussion record unit: records the discussion content, diagnosis opinions and final treatment plan during the consultation process;

[0117] Notification and reminder unit: Send consultation invitations and time change notifications to doctors participating in the consultation, and remind them before the consultation begins.

[0118] The interdisciplinary consultation platform module 26 also includes:

[0119] Intelligent matching unit: Using big data analysis technology, recommend a team of experts to participate in the consultation based on the patient's specific situation and historical data; using random forest or gradient boosting tree ensemble learning algorithms to extract the patient's age, gender, medical history, examination result characteristics, as well as the expert's professional background and historical consultation effect characteristics, use historical data to train the model, optimize hyperparameters through cross-validation, input new patient data, and the model outputs the most suitable expert list and confidence score

[0120] Permission management unit: ensure that only authorized users can access specific medical information, and protect data security and privacy; define the relationship between roles, permissions, and users, dynamically assign permissions based on user roles, and ensure that only authorized users can access specific resources

[0121] Remote Operation Guidance Unit: Provides doctors in remote areas with operation guidance for remote surgery and complex examinations, and realizes an intuitive teaching experience through AR / VR technology.

[0122] The interdisciplinary consultation platform module 26 also includes:

[0123] Decision support system unit: Integrates the latest medical guidelines, clinical trial results, and big data analysis to provide a scientific basis for decision-making during the consultation process; extracts key information from the literature through natural language processing (NLP) technology, and combines it with the patient's specific data to generate personalized treatment recommendations;

[0124] Follow-up plan generation unit: automatically generates a follow-up confirmation plan based on the consultation results, and synchronizes it to the doctor's mobile terminal (3), the medical mobile terminal 4 and the patient's mobile terminal 5 to ensure continuous tracking of the patient's recovery; the follow-up plan includes regular check-ups, drug adjustments and lifestyle recommendations, and sets a reminder function;

[0125] Knowledge base update unit: regularly update the medical knowledge base within the consultation platform, including the latest research progress and treatment methods, to maintain the professionalism and timeliness of the platform; automatically capture and integrate the latest research results by subscribing to authoritative medical journals and databases for reference during consultation;

[0126] Quality Assessment and Feedback Unit: Collect feedback after consultation, evaluate the consultation process and service quality, and continuously improve the consultation process and service level through questionnaire surveys and data analysis.

[0127] It should be noted that, in this article, 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 such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0128] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein. Any modification, replacement, and improvement made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. Intelligent cardiovascular disease diagnosis and treatment auxiliary system, characterized by: It includes a hospital server terminal (1), a cardiovascular disease intelligent diagnosis and treatment cloud platform (2), a doctor's mobile terminal (3), a medical mobile terminal (4) and a patient's mobile terminal (5); The hospital server terminal (1) includes a medical record model building module (11), which is used to compile clinical patient medical records created and uploaded by doctors and data uploaded by medical staff on clinical examinations of patients, and to create a patient medical record model. Each hospital server terminal (1) uploads the created medical record model to the cardiovascular disease intelligent diagnosis and treatment cloud platform (2) to collect cardiovascular case big data; The doctor's mobile terminal (3) includes a medical record establishment module (31) for the doctor to establish the medical record of a clinical patient. The doctor can obtain and browse cardiovascular cases in the cardiovascular disease intelligent diagnosis and treatment cloud platform (2) through the doctor's mobile terminal (3); The medical mobile terminal (4) comprises an electrocardiogram data acquisition unit (41), an ultrasound cardiogram acquisition unit (42), a blood test data acquisition unit (43), a cardiac magnetic resonance imaging acquisition unit (44), and a cardiovascular angiography acquisition unit (45), and is used by medical workers to upload clinical patient symptom data acquired through medical testing instruments, wherein the symptom data comprises electrocardiogram data, ultrasound cardiogram data, blood test data, cardiac magnetic resonance imaging data, and cardiovascular angiography data; Patient mobile terminal (5), used for patients and their family members to obtain health status and symptom data in real time; The cardiovascular disease intelligent diagnosis and treatment cloud platform (2) comprises a patient data modeling and recording module (21), a cardiovascular health analysis, detection and early warning module (22), a cardiovascular disease patient treatment method feedback module (23), a database (24) and a patient survival rate prediction module (25); The patient data modeling and recording module (21) comprises a patient data uploading and collecting unit (211) and a patient cardiovascular image modeling unit (212), which are used to obtain the data of the medical record model uploaded by the mobile terminal and manage the data of the medical record model; the patient cardiovascular image modeling unit (212) processes the collected patient examination data and constructs an image model; The cardiovascular health analysis, detection and early warning module (22) is used to analyze the acquired patient medical record data and examination data, determine whether the patient's cardiovascular health is healthy, collect cardiovascular abnormality data and issue an early warning; The cardiovascular disease treatment means feedback module (23) is used to analyze the cardiovascular abnormality data and retrieve treatment means for the same type of cardiovascular abnormality in the database (24); The database (24) comprises a medical record model storage module (241), a treatment means storage unit (242), a normal cardiovascular health big data storage unit (243), a healthy cardiovascular image model storage unit (244) and a patient cure and death record storage unit (245), and is used to store the medical record model data and the treatment means corresponding to the medical record, store the normal cardiovascular big data of healthy people, and record and store the duration of the patient cure and death in the medical record model data; The patient survival rate prediction module (25) is used to analyze the data of the cardiovascular disease, retrieve and call the database (24) for the cured and deceased data of the same type of cardiovascular disease, and predict the patient's survival rate through big data calculation.

2. The intelligent cardiovascular disease diagnosis and treatment auxiliary system according to claim 1, characterized in that: The medical record creation module (31) includes a patient basic information entry module (311), a patient pathological characteristics acquisition module (312), a treatment method entry module (313) and a medication information entry module (314), and is used by doctors to create medical records for clinical patients and enter the patient's basic information, pathological characteristics, treatment methods and medication information.

3. The intelligent cardiovascular disease diagnosis and treatment auxiliary system according to claim 1, characterized in that: The medical mobile terminal (4) comprises an electrocardiogram data acquisition unit (41), an ultrasound cardiogram data acquisition unit (42), a blood test data acquisition unit (43), a cardiac magnetic resonance imaging acquisition unit (44) and a cardiovascular angiography acquisition unit (45), and is used by medical personnel to acquire electrocardiogram data, ultrasound cardiogram data, blood test data, cardiac magnetic resonance imaging data and cardiovascular angiography data of clinical patients.

4. The intelligent cardiovascular disease diagnosis and treatment auxiliary system according to claim 1, characterized in that: The cardiovascular health analysis detection and early warning module (22) further comprises a patient data proofreading and analysis unit (221), a cardiovascular image model proofreading and analysis unit (222), an abnormal data recording unit (223) and an abnormal alarm unit (224); The patient data proofreading and analysis unit (221) is used to obtain and analyze the patient's medical history data and examination data, so as to proofread and analyze the patient's examination data and the normal cardiovascular big data of healthy people, and determine whether the patient's cardiovascular system is healthy; The cardiovascular image model calibration and analysis unit (222) is used to obtain an image model constructed by analyzing patient examination data, call a healthy cardiovascular image model in a database (24), and perform calibration and analysis with the image model constructed by the patient examination data, so as to analyze and detect the patient's cardiovascular pathological characteristics; The abnormal data recording unit (223) is used to record and store the patient's abnormal cardiovascular data analyzed above; The abnormality alarm unit (224) is used to send a warning signal to the mobile terminal when a cardiovascular abnormality of the patient is analyzed, and the mobile terminal receives the warning signal and issues a clinical alarm.

5. The intelligent cardiovascular disease diagnosis and treatment auxiliary system according to claim 1, characterized in that: The cardiovascular disease patient treatment means feedback module (23) comprises a historical treatment means calling unit (231) for patients with similar diseases and a clinical treatment means uploading recording unit (232); The historical treatment method calling unit (231) for similar patients is used to retrieve and call treatment methods for similar cardiovascular abnormalities in the database (24) through the cardiovascular abnormality data, and send the called treatment methods for similar cardiovascular abnormalities to the mobile terminal for display, so as to assist clinical cardiovascular disease treatment; The clinical treatment means uploading record unit (232) is used to upload and record the clinical treatment means and medication records of the patient's cardiovascular abnormalities used by medical staff.

6. The intelligent cardiovascular disease diagnosis and treatment auxiliary system according to claim 1, characterized in that: The patient survival rate prediction module (25) comprises a patient cure time recording module (251), a patient death time recording module (252), a similar patient treatment time big data analysis unit (253) and a similar patient survival rate big data analysis unit (254); The patient recovery time recording module (251) is used to analyze the patient medical record model data and record the patient recovery time, and the patient recovery time data is stored in the patient recovery and death record storage unit (245) in the database (24); The patient death time recording module (252) is used to analyze the patient medical record model data and record the patient death time, and the patient death time data is stored in the patient cure and death record storage unit (245) in the database (24); The treatment time data analysis unit (253) for patients of the same type is used to retrieve and call the data on the time of cure of the same type of cardiovascular disease in the patient cure and death record storage unit (245) through the patient's cardiovascular disease data, and predict the patient's cure time through big data calculation; The big data analysis unit (254) for the survival rate of patients of the same type is used to retrieve and call up the death time data of the same type of cardiovascular diseases in the patient cure and death record storage unit (245) through the patient's cardiovascular disease data, and predict the patient's survival rate through big data calculation.

7. The intelligent cardiovascular disease diagnosis and treatment auxiliary system according to claim 1, characterized in that: The doctor mobile terminal (3), the medical care mobile terminal (4) and the patient mobile terminal (5) are all provided with a patient clinical medical record data calling module (6), a module for obtaining treatment methods for the same type of disease (7), an early warning prompt module (8) and a display module (9); The patient clinical medical record data calling module (6) is used for doctors, medical staff and patient family members to obtain the patient medical records in the hospital server terminal (1) through a mobile terminal; The module for acquiring treatment methods for the same type of diseases (7) is used by doctors and medical workers to acquire big data of treatment methods for the same type of diseases in the cardiovascular disease intelligent diagnosis and treatment cloud platform (2); The early warning prompt module (8) is used to provide early warning prompts when cardiovascular abnormalities occur to the doctor's mobile terminal (3), the medical mobile terminal (4) and the patient's mobile terminal (5); The display module (9) is used for the doctor's mobile terminal (3), the medical mobile terminal (4) and the patient's mobile terminal (5) to obtain and display medical record data and treatment methods.

8. The intelligent cardiovascular disease diagnosis and treatment auxiliary system according to claim 1, characterized in that: It also includes an interdisciplinary consultation platform module (26), which is arranged inside the hospital server terminal (1) and includes the following units: Multidisciplinary Expert Invitation Unit: Use a combination of content-based recommendation algorithms and collaborative filtering algorithms to match patients with their professional fields by analyzing their medical records; Calculation process: The patient's medical record data is represented as a feature vector p = (p1, p2, ..., p n ), where each p i represents a specific symptom and examination result, and the expert's professional field is also represented as a feature vector e = (e1, e2, ..., e m ), the degree of matching is determined by calculating the cosine similarity, Recommend expert doctors based on historical consultation records. Calculation process: Construct a user-item matrix R, where R ij Represents the evaluation of the i-th patient on the j-th expert. Use matrix decomposition method to predict unknown scores: R≈PQ T , where P and Q are low-dimensional representations of users and items respectively; Video conferencing unit: provides high-definition video conferencing function, supporting multi-party real-time communication and discussion; File Sharing and Collaboration Unit: allows participants to upload, view and edit relevant medical documents; Case discussion record unit: records the discussion content, diagnosis opinions and final treatment plan during the consultation process; Notification and reminder unit: Send consultation invitations and time change notifications to doctors participating in the consultation, and remind them before the consultation begins.

9. The intelligent cardiovascular disease diagnosis and treatment auxiliary system according to claim 8, characterized in that: The interdisciplinary consultation platform module (26) further includes: Intelligent matching unit: using big data analysis technology to recommend a team of experts to participate in the consultation based on the patient's specific situation and historical data; Permission management unit: ensures that only authorized users can access specific medical information, ensuring data security and privacy; Remote Operation Guidance Unit: Provides doctors in remote areas with operation guidance for remote surgery and complex examinations, and realizes an intuitive teaching experience through AR / VR technology.

10. The intelligent cardiovascular disease diagnosis and treatment auxiliary system according to claim 9, characterized in that: The interdisciplinary consultation platform module (26) also includes: Decision support system unit: Integrates the latest medical guidelines, clinical trial results, and big data analysis to provide a scientific basis for decision-making during the consultation process. It extracts key information from the literature through natural language processing technology and generates personalized treatment recommendations based on the patient's specific data. Follow-up plan generation unit: automatically generates a follow-up confirmation plan based on the consultation results, and synchronizes it to the doctor's mobile terminal (3), the medical mobile terminal (4) and the patient's mobile terminal (5) to ensure continuous tracking of the patient's recovery; the follow-up plan includes regular check-ups, medication adjustments and lifestyle recommendations, and a reminder function is set; Knowledge base update unit: regularly update the medical knowledge base within the consultation platform, including the latest research progress and treatment methods, to maintain the professionalism and timeliness of the platform; automatically capture and integrate the latest research results by subscribing to authoritative medical journals and databases for reference during consultation; Quality Assessment and Feedback Unit: Collect feedback after consultation, evaluate the consultation process and service quality, and continuously improve the consultation process and service level through questionnaire surveys and data analysis.

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