Voice navigation method, device and equipment for recommending doctor seeing department based on illness state

Abstract

The invention provides a voice navigation method and device for recommending a doctor-seeing department based on the illness state and electronic equipment, and relates to the technical field of intelligent medical treatment, and the method comprises the steps: obtaining illness state data of a patient; analyzing the illness state data of the patient to obtain illness state keywords; and determining a recommended doctor-seeing department based on the disease keyword, displaying related information of the recommended doctor-seeing department to the patient, and broadcasting navigation information from the current position of the patient to the recommended doctor-seeing department by voice. The oral illness state of the patient is accurately obtained through the voice recognition technology, disease keywords are rapidly matched, and the most suitable doctor-seeing department is intelligently recommended based on the keywords.

Description

Technical Field

[0001] The present invention relates to the field of intelligent medical technology, and particularly to a voice navigation method, device and electronic device for recommending a department for medical treatment based on the condition of a patient. Background Art

[0002] In the current medical environment, the traditional methods for hospital department navigation and condition matching mainly include manual consultation, static signs and maps, and existing digital navigation systems. However, these traditional methods all have significant limitations and deficiencies in practical applications and are difficult to meet the growing and increasingly diverse medical needs.

[0003] Although the manual consultation method can provide personalized department recommendations according to the specific situation of patients, its service efficiency is limited by the number and professional level of staff. During the peak medical treatment period, long queues often form in front of the manual consultation windows, which not only reduces the medical treatment experience of patients, but also brings great pressure to the staff. At the same time, the information accuracy of manual consultation completely depends on the knowledge reserve of the staff. Once there is a knowledge blind spot or memory oversight, it may lead to inaccurate information transmission and affect the medical treatment decision-making of patients.

[0004] As traditional navigation tools in hospitals, static signs and maps can provide basic location information of departments, but lack the ability of real-time update and personalized customization. For patients who are seeing a doctor for the first time or are not familiar with the hospital layout, it is often time-consuming and laborious to find the correct department relying on static signs and maps and it is easy to get lost. In addition, these traditional navigation methods cannot perform intelligent matching according to the specific condition of patients and cannot meet the personalized medical treatment needs of patients.

[0005] Although existing digital navigation systems have improved the efficiency and accuracy of navigation, their operation interfaces are often complex and difficult to use for patients who are not familiar with the operation of electronic devices. Patients need to manually input or select various information during the navigation process, and the operation is cumbersome and error-prone. At the same time, most of these systems lack voice interaction functions and cannot provide truly intelligent navigation services. Patients cannot fully enjoy the convenience and comfort brought by technology during the medical treatment process.

[0006] Therefore, a voice navigation method, device and electronic device for recommending a department for medical treatment based on the condition of a patient are proposed. Summary of the Invention

[0007] The present invention provides a voice navigation method, device and electronic device for intelligent recognition and recommendation based on the condition of a patient, which accurately obtains the oral condition of the patient through voice recognition technology, quickly matches the disease keywords, and intelligently recommends the most suitable department for medical treatment based on these keywords.

[0008] This specification provides a voice navigation method for recommending medical departments based on the patient's condition, including:

[0009] Obtain the patient's condition data;

[0010] Analyze the patient's condition data to obtain disease keywords;

[0011] Based on the disease keywords, determine the recommended medical departments, display the relevant information of the recommended medical departments to the patient, and voice broadcast the navigation information from the patient's current location to the recommended medical departments.

[0012] Optionally, the analyzing the patient's condition data to obtain disease keywords includes:

[0013] The patient's condition data includes oral condition voice data;

[0014] Perform audio feature analysis on the oral condition voice data to obtain audio analysis results;

[0015] Convert the oral condition voice data into oral condition text data;

[0016] Combine the audio analysis results and the oral condition text data, and match them with the disease database to obtain disease keywords.

[0017] Optionally, the determining the recommended medical departments based on the disease keywords and displaying the relevant information of the recommended medical departments to the patient includes:

[0018] When determining no less than two recommended medical departments based on the disease keywords, perform a priority ranking on several recommended medical departments in combination with the patient's historical data, and display the relevant information of the recommended medical departments to the patient according to the priority ranking of the recommended medical departments.

[0019] Optionally, the determining the recommended medical departments based on the disease keywords and displaying the relevant information of the recommended medical departments to the patient includes:

[0020] When determining no less than two recommended medical departments based on the disease keywords, plan a recommended visit path for the patient in combination with the patient's current location and the relevant information of the recommended medical departments, and display the recommended visit path and the relevant information of the recommended medical departments to the patient.

[0021] Optionally, the determining the recommended medical departments based on the disease keywords and displaying the relevant information of the recommended medical departments to the patient includes:

[0022] When there are no less than two of the disease keywords, prioritize the disease keywords based on the disease knowledge graph, and determine the recommended departments for medical treatment based on different disease keywords;

[0023] Sort the recommended departments for medical treatment according to the priority order of the disease keywords, and display the relevant information of the recommended departments for medical treatment to the patient according to the order.

[0024] Optionally, it further includes:

[0025] After the patient goes to the recommended department for medical treatment, obtain the patient's examination data;

[0026] Analyze the patient's examination data to obtain abnormal parameter items and their parameter values;

[0027] Judge whether the parameter value corresponding to the abnormal parameter item meets the medical treatment parameter range;

[0028] When the parameter value corresponding to the abnormal parameter item meets the medical treatment parameter range, analyze the abnormal parameter item to determine the disease keyword corresponding to the abnormal parameter item;

[0029] Judge whether the disease keyword corresponding to the abnormal parameter item is a new keyword;

[0030] When the disease keyword corresponding to the abnormal parameter item is a new keyword, determine the recommended department for medical treatment based on the new keyword, display the relevant information of the recommended department for medical treatment to the patient, and voice broadcast the navigation information from the patient's current location to the recommended department for medical treatment.

[0031] Optionally, it further includes:

[0032] When the patient does not go to the recommended department for medical treatment within the preset time, send a reminder message and an information about the risk of not seeking medical treatment to the patient.

[0033] This specification provides a voice navigation device for recommending departments for medical treatment based on the disease condition, including:

[0034] An acquisition module, configured to acquire the patient's disease condition data;

[0035] An analysis module, configured to analyze the patient's disease condition data to obtain disease keywords;

[0036] A navigation module, configured to determine the recommended departments for medical treatment based on the disease keywords, display the relevant information of the recommended departments for medical treatment to the patient, and voice broadcast the navigation information from the patient's current location to the recommended departments for medical treatment.

[0037] Optionally, the analysis module includes:

[0038] The patient's condition data includes oral condition voice data;

[0039] Perform audio feature analysis on the oral condition voice data, and the audio analysis result;

[0040] Convert the oral condition voice data into oral condition text data;

[0041] Combine the audio analysis result and the oral condition text data, match with the disease database, and obtain disease keywords.

[0042] Optionally, the navigation module includes:

[0043] When determining no less than two of the recommended departments for treatment based on the disease keywords, perform priority sorting on several of the recommended departments for treatment in combination with the patient's historical data, and display the relevant information of the recommended departments for treatment to the patient according to the priority sorting of the recommended departments for treatment.

[0044] Optionally, the navigation module includes:

[0045] When determining no less than two of the recommended departments for treatment based on the disease keywords, plan a recommended treatment path for the patient in combination with the patient's current location and the relevant information of the recommended departments for treatment, and display the recommended treatment path and the relevant information of the recommended departments for treatment to the patient.

[0046] Optionally, the navigation module includes:

[0047] When there are no less than two disease keywords, perform priority sorting on the disease keywords based on the disease knowledge graph, and determine the recommended departments for treatment based on different disease keywords;

[0048] Sort the recommended departments for treatment according to the priority sorting of the disease keywords, and display the relevant information of the recommended departments for treatment to the patient according to the sorting.

[0049] Optionally, it further includes:

[0050] After the patient goes to the recommended department for treatment, obtain the patient's examination data;

[0051] Analyze the patient's examination data to obtain the abnormal parameter items and their parameter values;

[0052] Judge whether the parameter value corresponding to the abnormal parameter item meets the range of the treatment parameters;

[0053] When the parameter value corresponding to the abnormal parameter item meets the range of the treatment parameters, analyze the abnormal parameter item to determine the disease keyword corresponding to the abnormal parameter item;

[0054] Determine whether the disease keyword corresponding to the abnormal parameter item is a newly added keyword;

[0055] When the disease keyword corresponding to the abnormal parameter item is a newly added keyword, determine the recommended department for medical treatment based on the newly added keyword, display the relevant information of the recommended department for medical treatment to the patient, and voice broadcast the navigation information from the patient's current location to the recommended department for medical treatment.

[0056] Optionally, it further includes:

[0057] When the patient does not go to the recommended department for medical treatment within the preset time, send a reminder message and a risk information of non-medical treatment to the patient.

[0058] This specification also provides an electronic device, wherein the electronic device includes:

[0059] A processor; and,

[0060] A memory storing computer-executable instructions, and the executable instructions, when executed, cause the processor to execute any one of the above methods.

[0061] This specification also provides a computer-readable storage medium, wherein the computer-readable storage medium stores one or more programs, and the one or more programs, when executed by a processor, implement any one of the above methods.

[0062] The present invention integrates intelligent medical treatment, advanced speech recognition and multi-modal data processing technologies. By acquiring and analyzing the speech data of the patient's oral illness, combining multi-modal data such as biosensor data, wearable device data and gene data, and using advanced machine learning algorithms for fusion and analysis, it accurately extracts disease keywords and constructs a comprehensive and accurate patient illness portrait. Furthermore, based on the dynamically updated illness knowledge graph, combining patient information, hospital real-time resource scheduling situation and patient emotional factors, it intelligently recommends the most suitable department for medical treatment. At the same time, the present invention can also provide the patient with a detailed voice navigation service from the current location to the recommended department for medical treatment, and introduce virtual reality (VR) and augmented reality (AR) technologies to provide an immersive online consultation and illness simulation experience. In addition, the present invention also establishes a patient community to facilitate patients to share medical experience, communicate about illness and treatment experience. At the same time, it improves the follow-up and reminder mechanism after medical treatment, provides personalized medical treatment reminders and rehabilitation suggestions for patients, and introduces remote monitoring technology to monitor the patient's illness in real time. In terms of data security and privacy protection, the present invention adopts encryption technology and strict access control mechanisms to ensure the security and privacy of patient data. The present invention is proposed to comprehensively improve the patient's medical treatment experience and the intelligent level of medical services, and inject new vitality into the development of the intelligent medical field. Description of the Drawings

[0063] To more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0064] Figure 1 Schematic diagram of the principle of a voice navigation method for recommending a department for medical treatment based on the condition provided in the embodiments of this specification;

[0065] Figure 2 Schematic diagram of the structure of a voice navigation device for recommending a department for medical treatment based on the condition provided in the embodiments of this specification;

[0066] Figure 3 Schematic diagram of the structure of an electronic device provided in the embodiments of this specification;

[0067] Figure 4 Schematic diagram of the principle of a computer-readable medium provided in the embodiments of this specification. Detailed implementation manners

[0068] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art can think of other obvious variations. The basic principles defined in the following description can be applied to other implementation schemes, variant schemes, improvement schemes, equivalent schemes, and other technical schemes that do not deviate from the spirit and scope of the present invention.

[0069] The following is combined with the attached Figures 1-4 Describe the exemplary embodiments of the present invention more comprehensively. However, the exemplary embodiments can be implemented in various forms and should not be understood that the present invention is limited to the embodiments described herein. On the contrary, providing these exemplary embodiments can make the present invention more comprehensive and complete, and more convenient to convey the inventive concept to those skilled in the art. The same reference numerals in the figures represent the same or similar elements, components, or parts, and thus the repeated description of them will be omitted.

[0070] On the premise of conforming to the technical concept of the present invention, the features, structures, characteristics, or other details described in a specific embodiment do not exclude being combined in a suitable manner in one or more other embodiments.

[0071] In the description of specific embodiments, the features, structures, characteristics or other details described in the present invention are for enabling those skilled in the art to fully understand the embodiments. However, it does not exclude that those skilled in the art can practice the technical solutions of the present invention without one or more of the specific features, structures, characteristics or other details.

[0072] The flowcharts shown in the accompanying drawings are only illustrative and not necessarily include all the contents and operations / steps, nor are they necessarily executed in the described order. For example, some operations / steps can be decomposed, while some operations / steps can be combined or partially combined, so the actual execution order may change according to the actual situation.

[0073] The block diagrams shown in the accompanying drawings are only functional entities and not necessarily corresponding to physically independent entities. That is, these functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor devices and / or microcontroller devices.

[0074] The term "and / or" or "and / or" includes all combinations of any one or more of the associated listed items.

[0075] Figure 1 A schematic diagram of the principle of a voice navigation method for recommending a visiting department based on the patient's condition provided for the embodiments of this specification. This method may include:

[0076] S110: Obtain patient condition data;

[0077] Optionally, the patient condition data includes patient oral condition voice data, patient condition image data, patient condition text data, and patient current biological monitoring data.

[0078] In the specific embodiments of this specification, the patient condition image data includes various forms, commonly including X-ray films, CT scan images, magnetic resonance imaging (MRI), and ultrasonic images, etc. Taking a fracture patient as an example, the X-ray film clearly presents the fracture position of the bone and the direction of the fracture line, helping the doctor judge the severity of the fracture; the CT scan image can further show the fine internal structure of the bone and the damage of the surrounding tissues, such as whether there are bone fragments embedded in the surrounding muscles, nerves, blood vessels and other tissues, which is crucial for the accurate diagnosis of complex fractures and the formulation of surgical plans. MRI images have outstanding advantages in the diagnosis of nervous system and soft tissue diseases, and can accurately display brain lesions, joint soft tissue injuries, etc. For example, for patients with brain tumors, the MRI images can clearly outline the size, shape, position of the tumor and the boundary relationship with the surrounding brain tissues. Ultrasonic images are mostly used for the preliminary screening of diseases in the abdomen, cardiovascular and other parts, such as observing the development of the fetus in the pregnant woman's abdomen and detecting the opening and closing state of the heart valve.

[0079] The patient's condition text data can be text information about the condition input by the patient through terminal devices in the hospital (such as self-service machines, tablets, etc.) or mobile devices (such as mobile phone apps, etc.).

[0080] On the premise of ensuring the patient's right to know and obtaining their consent, the system will integrate the data collected from biosensors and wearable devices, and at the same time obtain the patient's genetic data, so as to enrich the patient's condition data system and provide a more comprehensive and accurate basis for subsequent diagnosis and treatment.

[0081] The patient's oral condition voice data. Specifically, in key areas of the hospital, such as the registration hall, waiting area, etc., dedicated system terminals are set up. These terminals are equipped with high-quality microphones and speakers to ensure the clarity of voice input and the accuracy of output. Patients can also access the mobile application of the system through mobile devices such as mobile phones. The mobile application interface is simple and clear, easy to operate, and at the same time supports the voice input function. When the patient starts the system (either through the terminal or the mobile application), the system will automatically load the necessary programs and algorithms and be ready to receive the user's voice input. At this time, the system interface will display a clear prompt, informing the patient that they can input their symptoms or needs through voice.

[0082] For patients using the system for the first time, the system will guide them through a simple registration process. During the registration process, the patient needs to input some basic information, such as name, gender, age, etc., and set an account password. This information will be used for subsequent login and personalized services. Registered patients can quickly log in to the system through the account password or mobile phone number verification code. After successful login, the system will automatically load the patient's personal information to provide personalized department recommendations and navigation in subsequent services.

[0083] After the patient faces the system terminal or opens the mobile application, the system will automatically enter the voice input mode. At this time, the microphone will start capturing the patient's voice input. The patient can directly describe their symptoms or needs through voice. For example, the patient can say: "I have a terrible headache and want to register for medical treatment." Or "I feel uncomfortable in my stomach. Maybe I ate something bad." The system will receive and process the patient's voice input in real time. To ensure the accuracy and integrity of the voice data, the system may adopt some preprocessing technologies, such as noise cancellation, voice enhancement, etc. While receiving the voice input, the system interface will display a recording prompt to inform the patient that the system is receiving their voice input.

[0084] S120: Analyze the patient's condition data to obtain disease keywords;

[0085] Optionally, the S120 includes:

[0086] The patient's condition data includes oral condition voice data;

[0087] Perform audio feature analysis on the oral condition voice data to obtain the audio analysis results;

[0088] Convert the oral condition voice data into oral condition text data;

[0089] Combine the audio analysis results and the oral condition text data, and match them with the disease database to obtain disease keywords.

[0090] In the specific embodiments of this specification, advanced audio processing technology is used to perform audio feature analysis on the oral condition voice data, analyzing features such as the intonation, speech rate, volume change, and pause frequency of the speech. When the patient describes relatively severe or painful symptoms, the voice often involuntarily shows phenomena such as increased volume, accelerated speech rate, and frequent pauses. By capturing these audio features, it is possible to preliminarily judge the patient's degree of attention to different symptoms and emotional state. For example, if the patient's speech rate suddenly slows down and the intonation is low when mentioning a certain symptom, it may imply that the symptom has brought great trouble to him or there are concerns that are difficult to talk about. After rigorous audio analysis, finally obtain valuable audio analysis results.

[0091] Using intelligent speech conversion technology, accurately convert the oral condition voice data into oral condition text data for subsequent text processing and analysis. This conversion process not only requires a high degree of accuracy but also needs to retain the key semantic information in the speech to ensure that no details that may be related to the diagnosis are lost. For example, accurately convert the speech content with a local accent and colloquial expressions of the patient into a standard medical text expression.

[0092] Organically combine the obtained audio analysis results and the converted oral condition text data, and perform a comprehensive match with the pre-constructed disease database. The disease database contains a large amount of known disease information, covering the typical symptoms, onset characteristics, and related symptom combinations of various diseases. Through accurate matching, screen and extract the disease keywords most relevant to the current patient's condition. For example, if the audio analysis results show that the patient's intonation is rapid when describing the cough symptom, and the oral condition text data mentions that the cough is accompanied by yellow phlegm and fever, after matching with the disease database, disease keywords such as "respiratory tract infection" and "pneumonia" may be extracted, providing strong clues and directions for the doctor's further diagnosis.

[0093] S130: Determine the recommended department for medical treatment based on the disease keywords, display the relevant information of the recommended department for medical treatment to the patient, and voice broadcast the navigation information from the patient's current location to the recommended department for medical treatment.

[0094] Optionally, S130 includes:

[0095] When determining no less than two of the recommended departments based on the disease keywords, prioritize several of the recommended departments in combination with the patient's historical data, and display the relevant information of the recommended departments to the patient according to the priority ranking of the recommended departments.

[0096] In the specific implementation of this specification, when a symptom such as "headache" that may involve multiple departments is identified based on the disease keywords, it does not limit the recommendation to a single department, but instead activates a more intelligent and comprehensive recommendation mechanism. This mechanism comprehensively considers the patient's symptom description, age, gender, medical history, and any relevant special conditions, so as to be able to recommend multiple possible departments for treatment at the same time.

[0097] According to the preset disease knowledge graph, analyze and determine the departments most relevant to the "headache" symptom. For example, the Department of Neurology may be closely related to the headache symptom due to migraine, cerebrovascular diseases, etc., while the Department of Neurosurgery may be related to headache due to brain tumors, trauma, etc. The system can identify these potential department associations and give clear explanations or differentiation conditions when making recommendations.

[0098] When it is determined that there are no less than two recommended departments for treatment, the system will further prioritize these departments in combination with the patient's historical data, such as past medical records, diagnosis results, treatment effects, etc. This ranking process not only considers the direct relevance between the department and the disease, but also incorporates multiple factors such as the professional level of the department, patient satisfaction, treatment success rate, and current medical load. Through deep learning and data mining techniques, the system can generate a department ranking list that not only complies with medical guidelines but also meets the personalized needs of the patient.

[0099] When displaying the information of the recommended departments, the system will clearly list the names, professional features, possible treatment areas, and brief reasons for recommendation of each department in the order of priority. For example, the system may prompt: "For your 'headache' symptom, we recommend the following departments: First is the Department of Neurology, which has rich experience in dealing with migraine, cerebrovascular diseases, etc.; second is the Department of Neurosurgery, which will be an ideal choice if your headache may be related to brain tumors or trauma." Such a display method aims to help patients comprehensively understand the characteristics and advantages of each department, so as to make a more informed choice according to their own situation.

[0100] It should be noted that although the system provides intelligent department recommendations and priority rankings, the final choice still lies with the patient. The system encourages patients to comprehensively consider and independently select the most suitable department for consultation based on their symptoms, past medical experience, and any personal special needs. Such a design aims to ensure that patients have the greatest autonomy and satisfaction during the medical treatment process.

[0101] Optionally, S130 includes:

[0102] When determining no less than two of the recommended departments for consultation based on the disease keywords, combine the patient's current location and the relevant information of the recommended departments for consultation to plan a recommended consultation path for the patient, and display the recommended consultation path and the relevant information of the recommended departments for consultation to the patient.

[0103] In the specific implementation manner of this specification, the geographical information system (GIS) of the integrated hospital is integrated to obtain the accurate location of the patient in real time. At the same time, it will also be docked with the electronic medical record system (EMR) of each department to obtain key information such as the current number of registered patients, doctor scheduling, and estimated waiting time. This information provides the basis for the system to formulate the optimal consultation path.

[0104] After obtaining the patient's location and the real-time information of the departments, the system will perform complex calculations and analyses to determine the most suitable department for consultation and path for the patient. For example, for the symptom of "headache", if both the Department of Neurology and the Department of Neurosurgery are suitable departments for consultation, but the current number of registered patients in the Department of Neurology is less and it is closer to the patient, the system will give priority to recommending the Department of Neurology and plan the optimal path from the patient's current location to the Department of Neurology. When recommending the consultation path, the system will consider various factors, including walking distance, estimated arrival time, waiting time in the department, and possible traffic conditions, etc. By comprehensively considering these factors, the system can provide a fast and efficient consultation plan for the patient. Finally, the system will clearly display the recommended consultation path and the relevant information of the consultation department to the patient. This information may include the specific location of the department, walking route, estimated arrival time, registration situation, and doctor introduction, etc. Such a display method aims to help patients fully understand and make a quick choice, thereby shortening the medical treatment process and improving the medical treatment efficiency.

[0105] Optionally, S130 includes:

[0106] When the number of the disease keywords is no less than two, perform priority ranking on the disease keywords based on the disease knowledge graph, and determine the recommended departments for consultation based on different disease keywords;

[0107] Sort the recommended departments for medical treatment according to the priority order of the disease keywords, and display the relevant information of the recommended departments for medical treatment to the patient according to the order.

[0108] In the specific implementation manner of this specification, based on the pre-constructed disease knowledge graph, an intelligent priority order is performed on the identified disease keywords. This sorting process fully considers multiple factors such as the urgency of the symptoms, potential harmfulness, common diagnostic results, and their impact on the patient's daily life. For example, for a symptom like "sudden severe headache", the system may give it a higher priority because it may indicate serious health problems such as acute cerebrovascular diseases.

[0109] Optionally, it further includes:

[0110] After the patient goes to the recommended department for medical treatment, obtain the patient's examination data;

[0111] Analyze the patient's examination data to obtain the abnormal parameter items and their parameter values;

[0112] Judge whether the parameter value corresponding to the abnormal parameter item meets the medical treatment parameter range;

[0113] When the parameter value corresponding to the abnormal parameter item meets the medical treatment parameter range, analyze the abnormal parameter item to determine the disease keyword corresponding to the abnormal parameter item;

[0114] Judge whether the disease keyword corresponding to the abnormal parameter item is a new keyword;

[0115] When the disease keyword corresponding to the abnormal parameter item is a new keyword, determine the recommended department for medical treatment based on the new keyword, display the relevant information of the recommended department for medical treatment to the patient, and voice broadcast the navigation information from the patient's current location to the recommended department for medical treatment.

[0116] In the specific implementation of this specification, the system will be integrated with the hospital's examination result system to obtain and monitor the patient's various examination data in real time. These data cover the detailed results of various medical examinations received by the patient and are important bases for evaluating the patient's health status. Then, the system will conduct in-depth analysis on the obtained patient examination data. By comparing with the preset normal value range, it will identify abnormal parameter items and their specific parameter values. This step aims to accurately locate any situations where the patient's examination deviates from the normal range, laying a foundation for subsequent analysis and processing. Subsequently, the system will determine whether the parameter values corresponding to these abnormal parameter items meet the preset medical visit parameter range. This range is set based on medical knowledge and clinical experience and is used to distinguish between minor abnormalities and serious abnormalities that require further attention. If the parameter value of an abnormal parameter item exceeds the normal range and reaches the medical visit parameter range, the system will enter the next step of analysis. After confirming the abnormal parameter items, the system will use the disease knowledge graph and machine learning algorithms to conduct in-depth analysis on these abnormal parameter items to determine the corresponding disease keywords. This process comprehensively considers the nature of the abnormal parameters, the association patterns in historical data, as well as clinical guidelines and expert opinions to ensure the accuracy and reliability of the disease keywords. Next, the system will determine whether these disease keywords are new keywords, that is, whether they were not mentioned when the patient initially described the symptoms. If it is determined to be a new keyword, it means that the patient may have new symptoms or changes in the condition, requiring further medical attention. Based on these newly added disease keywords, the system will intelligently determine the recommended medical visit department. This recommendation process not only considers the direct relevance between the department and the disease, but also incorporates real-time information such as the professional level of the department, treatment experience, and current registration status to ensure the best medical visit advice for the patient. Finally, the system will clearly display the relevant information of the recommended medical visit department to the patient, including the department name, location, doctor team introduction, etc., and provide a voice broadcast function to broadcast the detailed navigation information from the patient's current location to the recommended medical visit department. Such a design aims to help the patient quickly understand and select the most suitable medical visit department for themselves, while providing a convenient navigation service, shortening the medical treatment process, and improving the medical treatment efficiency.

[0117] Optionally, it further includes:

[0118] When the patient does not go to the recommended medical visit department for medical treatment within the preset time, send a reminder message and a non-medical treatment risk message to the patient.

[0119] In the specific embodiments of this specification, it is monitored in real time or at regular intervals whether the patient has visited the recommended department for medical treatment. This can be achieved through the hospital's registration system, geographical information system (GIS) location data, or information actively provided by the patient. If within a preset time (such as one hour), the system does not detect a record of the patient visiting the recommended department or receive confirmation of the patient's visit, the system will determine that the patient has not visited the recommended department. The system will send a reminder message to the patient via text message, mobile application push, or voice call. This message will clearly indicate that the patient has not yet visited the recommended department and briefly explain the relevance of this department to the patient's condition. In the reminder message, the system will clearly inform the patient of the possible risks of not visiting the recommended department. These risks may include delayed treatment, aggravated condition, occurrence of complications, etc., which will be determined specifically according to the patient's disease keywords and disease knowledge graph. The reminder message will also emphasize again the importance of the recommended department and why this department is the most suitable choice for the patient at present. This helps the patient understand the basis of the system's recommendation and prompts them to reconsider whether to visit this department.

[0120] After a period of time (such as half an hour) after sending the reminder message, if the system still does not detect the patient's visit behavior, the system will recommend the relevant department to the patient again and emphasize its importance more strongly. This recommendation may include more detailed information, such as the professional characteristics of the department, introduction of the doctor team, etc., to increase the patient's trust and willingness to visit.

[0121] If the system determines that the patient's condition is very urgent and there are high risks (for example, the patient's disease keywords are highly related to serious diseases and the patient has not visited the recommended emergency department), the system will automatically notify the relevant medical staff or department head. The notification content may include the patient's basic information, overview of the condition, and the situation of not visiting, so that the medical staff can follow up in a timely manner and persuade the patient or take other necessary medical measures.

[0122] The system will record the patient's non-visiting behavior and the risk notification measures taken for subsequent analysis and optimization. At the same time, the system will collect the patient's feedback to understand their acceptance and satisfaction with the system's recommendation and reminder message.

[0123] Through terminal devices within the hospital (such as self-service machines, tablets, etc.) or mobile devices (such as mobile phone apps, etc.), combined with VR devices, patients can clearly hear the doctor's detailed analysis of the condition. Moreover, by using AR technology, abstract diseases and complex treatment processes can be intuitively presented in front of the eyes, so as to deeply understand the ins and outs of the condition and the corresponding treatment plan through an immersive experience, effectively eliminating the anxiety caused by information asymmetry.

[0124] Moreover, through mobile devices, patients can access the patient community, allowing patients to share medical experiences, exchange conditions and treatment insights among themselves, enhancing patients' sense of participation and belonging.

[0125] Deeply analyze the unique conditions of each patient, covering key elements such as disease types, severity, and development trends. Closely combine with their treatment progress, such as being in the surgical recovery period, different stages of chemotherapy, etc. At the same time, fully consider the actual operation status of the hospital, including the busy hours of each department, the schedule of expert outpatient services, etc. Based on this, use precise algorithms to customize personalized appointment reminders for patients to ensure that patients do not miss any key follow-up visits. Not only that, but also give targeted rehabilitation suggestions according to the individual situation of patients, from the reasonable collocation of daily diet, the detailed plan of moderate exercise, to the key points of psychological state adjustment, to fully assist patients on the road to recovery.

[0126] For patients with chronic diseases that require long-term treatment and follow-up, as well as special cases with complex and changeable conditions, remotely monitor technology is innovatively introduced. With the help of wearable medical devices and home intelligent monitoring instruments, core physiological indicators such as heart rate, blood pressure, blood sugar, and blood oxygen saturation of patients are collected in real-time and continuously, and the data is immediately transmitted back to the hospital's medical big data platform through a safe and stable transmission channel. The professional medical team relies on the intelligent analysis system to deeply mine and interpret these massive amounts of data, accurately grasping the dynamic progress of patients' conditions. Once abnormal fluctuations are detected, immediately provide professional medical advice to patients through various communication methods, such as text messages, phone calls, online medical APP push, etc., to guide them to take necessary emergency measures, and at the same time quickly organize a medical intervention plan, and adjust the subsequent treatment plan in a timely manner when necessary, truly realizing seamless guardianship of the entire course of patients, allowing medical care to cross time and space limitations, and escorting patients' health.

[0127] The present invention integrates intelligent healthcare, advanced speech recognition, and multi-modal data processing technologies. By acquiring and analyzing the speech data of a patient's oral description of their condition, combining multi-modal data such as biosensor data, wearable device data, and genetic data, and using advanced machine learning algorithms for fusion and analysis, it accurately extracts disease keywords and constructs a comprehensive and accurate patient condition portrait. Furthermore, based on a dynamically updated disease knowledge graph, combined with patient information, the real-time resource scheduling situation of the hospital, and the patient's emotional factors, it intelligently recommends the most suitable department for treatment. At the same time, the present invention can also provide a detailed voice navigation service for the patient from the current location to the recommended department for treatment, and introduce virtual reality (VR) and augmented reality (AR) technologies to provide an immersive online consultation and disease simulation experience. In addition, the present invention has established a patient community to facilitate the sharing of medical experience, the exchange of conditions, and treatment insights among patients. At the same time, it has improved the follow-up and reminder mechanism after treatment, providing personalized treatment reminders and rehabilitation suggestions for patients, and introducing remote monitoring technology to monitor the patient's condition in real time. In terms of data security and privacy protection, the present invention adopts encryption technology and a strict access control mechanism to ensure the security and privacy of patient data. The present invention is proposed to comprehensively improve the patient's medical experience and the intelligent level of medical services, injecting new vitality into the development of the intelligent healthcare field.

[0128] Figure 2 FIG. 4 is a schematic diagram of the principle of a voice navigation device for recommending a department for treatment based on a patient's condition provided by an embodiment of the present specification. The device may include:

[0129] An acquisition module 10, configured to acquire patient condition data;

[0130] An analysis module 20, configured to analyze the patient condition data to obtain disease keywords;

[0131] A navigation module 30, configured to determine a recommended department for treatment based on the disease keywords, display relevant information of the recommended department for treatment to the patient, and voice broadcast navigation information from the patient's current location to the recommended department for treatment.

[0132] Optionally, the analysis module 20 includes:

[0133] The patient condition data includes oral condition speech data;

[0134] Perform audio feature analysis on the oral condition speech data to obtain an audio analysis result;

[0135] Convert the oral condition speech data into oral condition text data;

[0136] Combine the audio analysis result and the oral condition text data, and match them with a disease database to obtain disease keywords.

[0137] Optionally, the navigation module 30 includes:

[0138] When determining no less than two of the recommended departments for consultation based on the disease keywords, prioritize several of the recommended departments for consultation in combination with the patient's historical data, and display the relevant information of the recommended departments for consultation to the patient according to the priority ranking of the recommended departments for consultation.

[0139] Optionally, the navigation module 30 includes:

[0140] When determining no less than two of the recommended departments for consultation based on the disease keywords, plan a recommended visit route for the patient in combination with the patient's current location and the relevant information of the recommended departments for consultation, and display the recommended visit route and the relevant information of the recommended departments for consultation to the patient.

[0141] Optionally, the navigation module 30 includes:

[0142] When there are no less than two disease keywords, prioritize the disease keywords based on the disease knowledge graph, and determine the recommended departments for consultation based on different disease keywords;

[0143] Sort the recommended departments for consultation according to the priority ranking of the disease keywords, and display the relevant information of the recommended departments for consultation to the patient according to the ranking.

[0144] Optionally, it further includes:

[0145] After the patient goes to the recommended department for consultation, obtain the patient's examination data;

[0146] Analyze the patient's examination data to obtain abnormal parameter items and their parameter values;

[0147] Judge whether the parameter value corresponding to the abnormal parameter item meets the consultation parameter range;

[0148] When the parameter value corresponding to the abnormal parameter item meets the consultation parameter range, analyze the abnormal parameter item to determine the disease keyword corresponding to the abnormal parameter item;

[0149] Judge whether the disease keyword corresponding to the abnormal parameter item is a new keyword;

[0150] When the disease keyword corresponding to the abnormal parameter item is a new keyword, determine the recommended department for consultation based on the new keyword, display the relevant information of the recommended department for consultation to the patient, and voice broadcast the navigation information from the patient's current location to the recommended department for consultation.

[0151] Optionally, it further includes:

[0152] When the patient fails to visit the recommended department for medical treatment within the preset time, a reminder message and an information on the risk of non-visiting are sent to the patient.

[0153] The functions of the device according to the embodiments of the present invention have been described in the above method embodiments. Therefore, for the details not described in this embodiment, reference may be made to the relevant descriptions in the foregoing embodiments, which will not be elaborated herein.

[0154] Based on the same inventive concept, the embodiments of the present specification further provide an electronic device.

[0155] The embodiments of the electronic device of the present invention are described below. The electronic device can be regarded as a specific physical implementation manner of the above method and device embodiments of the present invention. For the details described in the embodiments of the electronic device of the present invention, they should be regarded as a supplement to the above method or device embodiments; for the details not disclosed in the embodiments of the electronic device of the present invention, reference may be made to the above method or device embodiments for implementation.

[0156] Figure 3 The structural schematic diagram of an electronic device provided for the embodiments of the present specification is as follows. Refer to Figure 3 to describe the electronic device 300 according to this embodiment of the present invention. Figure 3 The shown electronic device 300 is only an example and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.

[0157] As Figure 3 shown, the electronic device 300 is presented in the form of a general-purpose computing device. The components of the electronic device 300 may include but are not limited to: at least one processing unit 310, at least one storage unit 320, a bus 330 connecting different system components (including the storage unit 320 and the processing unit 310), a display unit 340, etc.

[0158] Among them, the storage unit stores program codes, and the program codes can be executed by the processing unit 310, so that the processing unit 310 executes the steps according to various exemplary embodiments of the present invention described in the above processing method part. For example, the processing unit 310 can execute the steps as Figure 1 shown.

[0159] The storage unit 320 may include a readable medium in the form of a volatile storage unit, such as a random access storage unit (RAM) 3201 and / or a cache storage unit 3202, and may further include a read-only storage unit (ROM) 3203.

[0160] The storage unit 320 may further include a program / utility 3204 having a set (at least one) of program modules 3205. Such program modules 3205 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment.

[0161] The bus 330 may represent one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus structures.

[0162] The electronic device 300 may also communicate with one or more external devices 400 (such as a keyboard, a pointing device, a Bluetooth device, etc.), may also communicate with one or more devices that enable a viewer to interact with the electronic device 300, and / or may communicate with any device that enables the electronic device 300 to communicate with one or more other computing devices (such as a router, a modem, etc.). Such communication may be carried out through the input / output (I / O) interface 350. Moreover, the electronic device 300 may also communicate with one or more networks (such as a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) through the network adapter 360. The network adapter 360 may communicate with other modules of the electronic device 300 through the bus 330. It should be understood that although Figure 3 not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 300, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, etc.

[0163] Through the description of the above embodiments, those skilled in the art can easily understand that the exemplary embodiments described in the present invention can be implemented by software, or can be implemented by the way of software combined with necessary hardware. Therefore, the technical solutions according to the embodiments of the present invention can be embodied in the form of a software product, which can be stored in a computer-readable storage medium (which may be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (which may be a personal computer, a server, or a network device, etc.) to execute the above method according to the present invention. When the computer program is executed by a data processing device, the computer-readable medium can implement the above method of the present invention, that is: as Figure 1 shown in the method.

[0164] Figure 4 It is a schematic diagram of the principle of a computer-readable medium provided by the embodiments of this specification.

[0165] ImplementFigure 1 The computer program of the method shown can be stored on one or more computer-readable media. The computer-readable media can be a readable signal medium or a readable storage medium. The readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0166] The computer-readable storage medium can include a data signal propagated in a baseband or as part of a carrier wave, in which the readable program code is carried. Such a propagated data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The readable storage medium can also be any readable medium other than the readable storage medium, which can send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the readable storage medium can be transmitted using any appropriate medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination of the above.

[0167] The program code for performing the operations of the present invention can be written in any combination of one or more programming languages, including object-oriented programming languages such as Java, C++, etc., and also including conventional procedural programming languages such as the "C" language or similar programming languages. The program code can be executed entirely on the viewer's computing device, partially on the viewer's device, executed as a stand-alone software package, partially on the viewer's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the viewer's computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, by using an Internet service provider to connect through the Internet).

[0168] In summary, the present invention can be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art should understand that general-purpose data processing devices such as microprocessors or digital signal processors (DSPs) can be used in practice to implement some or all of the functions of some or all of the components in the embodiments of the present invention. The present invention can also be implemented as a device or apparatus program (e.g., a computer program and a computer program product) for executing some or all of the methods described herein. Such a program for implementing the present invention can be stored on a computer-readable medium, or can be in the form of one or more signals. Such signals can be downloaded from an Internet website, or provided on a carrier signal, or in any other form.

[0169] The specific embodiments described above further elaborate on the purpose, technical solutions, and beneficial effects of the present invention. It should be understood that the present invention is not inherently related to any specific computer, virtual device, or electronic device, and various general-purpose devices can also implement the present invention. The above are only specific embodiments of the present invention and are not used to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

[0170] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other. Each embodiment focuses on the differences from other embodiments.

[0171] The above are only embodiments of the present application and are not used to limit the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application shall be included within the scope of the claims of the present application.

Claims

1. A voice navigation method for recommending a medical department based on the condition, characterized in that: include: Obtain patient condition data; Analyze the patient's condition data to obtain disease keywords; The recommended treatment department is determined based on the disease keywords, the relevant information of the recommended treatment department is displayed to the patient, and the navigation information from the patient's current location to the recommended treatment department is voice broadcast.

2. The voice navigation method for recommending a medical department based on the condition of the patient as claimed in claim 1, characterized in that: The patient's condition data is analyzed to obtain condition keywords, including: The patient's condition data includes oral condition voice data; Performing audio feature analysis on the oral medical condition voice data and obtaining audio analysis results; Converting the spoken condition voice data into spoken condition text data; The audio analysis result and the oral condition text data are combined and matched with the condition database to obtain condition keywords.

3. The voice navigation method for recommending a medical department based on the condition of a patient as claimed in claim 2, characterized in that: The determining of the recommended medical department based on the symptom keyword and displaying the relevant information of the recommended medical department to the patient includes: When no less than two recommended medical departments are determined based on the disease keywords, the recommended medical departments are prioritized in combination with the patient's historical data, and the relevant information of the recommended medical departments is displayed to the patient according to the priority ranking of the recommended medical departments.

4. The voice navigation method for recommending a medical department based on the condition of a patient as claimed in claim 3, characterized in that: The determining of the recommended medical department based on the symptom keyword and displaying the relevant information of the recommended medical department to the patient includes: When at least two recommended medical departments are determined based on the disease keywords, a recommended medical route is planned for the patient in combination with the patient's current location and relevant information of the recommended medical departments, and the recommended medical route and relevant information of the recommended medical departments are displayed to the patient.

5. The voice navigation method for recommending a medical department based on the condition of a patient as claimed in claim 4, characterized in that: The determining of the recommended medical department based on the symptom keyword and displaying the relevant information of the recommended medical department to the patient includes: When there are no less than two disease keywords, the disease keywords are prioritized based on the disease knowledge graph, and the recommended consultation department is determined based on different disease keywords; The recommended treatment departments are sorted according to the priority of the disease keywords, and the relevant information of the recommended treatment departments is displayed to the patient according to the sorting.

6. The voice navigation method for recommending a medical department based on the condition of the patient as claimed in claim 5, characterized in that: Also includes: When the patient goes to the recommended department for treatment, obtaining the patient's examination data; Analyze the patient examination data to obtain abnormal parameter items and parameter values; Determine whether the parameter value corresponding to the abnormal parameter item meets the medical parameter range; When the parameter value corresponding to the abnormal parameter item meets the consultation parameter range, the abnormal parameter item is analyzed to determine the symptom keyword corresponding to the abnormal parameter item; Determine whether the symptom keyword corresponding to the abnormal parameter item is a newly added keyword; When the disease keyword corresponding to the abnormal parameter item is a newly added keyword, the recommended treatment department is determined based on the newly added keyword, the relevant information of the recommended treatment department is displayed to the patient, and the navigation information from the patient's current location to the recommended treatment department is voice broadcast.

7. The voice navigation method for recommending a medical department based on the condition of the patient as claimed in claim 6, characterized in that: Also includes: When the patient fails to visit the recommended department within the preset time, a reminder message and risk information of non-visit will be sent to the patient.

8. A voice navigation device for recommending a medical department based on the condition of a patient, characterized in that: include: An acquisition module is used to obtain the patient's condition voice data; An analysis module, used to analyze the patient's condition voice data to obtain disease keywords; The navigation module is used to determine the recommended treatment department based on the disease keywords, display relevant information of the recommended treatment department to the patient, and voice broadcast the navigation information from the patient's current location to the recommended treatment department.

9. An electronic device, wherein: The electronic device includes: processor; and, A memory storing computer executable instructions which, when executed, cause the processor to perform a method according to any one of claims 1-7.

10. A computer-readable storage medium, wherein: The computer-readable storage medium stores one or more programs, and when the one or more programs are executed by a processor, the method of any one of claims 1 to 7 is implemented.

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