Medical resource comparison method, device and equipment and computer readable medium

Abstract

This invention discloses a method, apparatus, device, and computer-readable medium for comparing medical resources, relating to the field of internet-based medical technology. One specific embodiment of the method includes: responding to an input target disease, displaying a list of doctors associated with the target disease; receiving a pre-selection operation on multiple doctors in the doctor list, establishing and displaying a pre-selected doctor list; responding to a doctor comparison instruction, inputting the doctors from the pre-selected doctor list into an artificial intelligence model based on preset multi-dimensional features, receiving and displaying the doctor comparison results, wherein the multi-dimensional features include one or more of the following: professional matching degree, doctor qualifications, patient satisfaction rate, consultation fees, and appointment time; responding to a target doctor selected in the doctor comparison results, displaying the consultation page of the target doctor. This embodiment enables the comparison of information from multiple doctors.

Description

Technical Field

[0001] This invention relates to the field of internet medical technology, and in particular to a method, apparatus, device, and computer-readable medium for comparing medical resources. Background Technology

[0002] With the deep integration of internet technology and medical services, online consultations have become an important part of the modern healthcare system, and have gradually become a key way to alleviate the strain on traditional medical resources and reduce patients' time and economic costs of seeking medical treatment. It has become a common trend for patients to use online platforms for disease consultations and remote treatments.

[0003] In implementing this invention, when selecting a doctor for online consultations, users often need to narrow down the selection based on department, doctor tags (such as top-tier hospitals, chief physicians), or rely on software systems for automatic selection. When users are interested in multiple doctors, it is often difficult to choose the one they need to consult. Summary of the Invention

[0004] In view of this, embodiments of the present invention provide a method, apparatus, device, and computer-readable medium for comparing medical resources, which can realize the comparison of information from multiple doctors.

[0005] To achieve the above objectives, according to one aspect of the present invention, a method for comparing medical resources is provided, applied to a patient, comprising: In response to the input of a target disease, a list of doctors associated with the target disease is displayed; Receive pre-selection operations for multiple doctors in the doctor list, and create and display the pre-selected doctor list; In response to a doctor comparison instruction, the system receives and displays the doctor comparison results under the multi-dimensional features in the doctor comparison instruction. The multi-dimensional features include one or more of the following: professional matching degree, doctor qualifications, patient satisfaction rate, consultation fee, and appointment time.

[0006] The step of receiving a pre-selection operation for multiple doctors in the doctor list, and establishing and displaying the pre-selected doctor list, includes: A preselection control is displayed in at least one of the doctor identifiers on the doctor list page and the doctor details page. The preselection control is in response to a preselection operation on at least one of the doctors on the doctor list page and the doctor details page, to create the preselected doctor list and add the doctor to the preselected doctor list. The preselection control scrolls with the page. And / or, In response to a batch pre-selection operation of multiple doctor identifiers on the doctor list page, the pre-selected doctor list is created and multiple doctors are added to the pre-selected doctor list.

[0007] The list of pre-selected doctors includes: The pre-selected doctor list includes multiple information units, which display doctor information and corresponding multi-dimensional features of the doctor. The information unit is equipped with a corresponding deletion control. In response to the operation of the deletion control, a deletion confirmation prompt is triggered to delete the corresponding information unit from the list of pre-selected doctors.

[0008] The response to the doctor's comparison instruction includes: In response to a doctor comparison command, if the number of doctors in the pre-selected doctor list does not reach a preset threshold, a prompt to add a doctor will be displayed. A pre-selection control is displayed at the doctor's identifier on the doctor list page or doctor details page. The pre-selection control, in response to a doctor addition instruction, adds the doctor to the pre-selected doctor list to execute the doctor comparison instruction.

[0009] The displayed doctor comparison results include one or more of the following: The multidimensional features are identified in a table, and the doctor's scores on the multidimensional features are displayed in the table; The doctor's overall score is indicated and displayed using different colors; The consultation suggestions are displayed and are determined using an artificial intelligence model based on the patient's basic medical characteristics, the scores of the multidimensional characteristics, and the doctor's comprehensive score. And / or, Following the display of the doctor comparison results under the multidimensional features in the doctor comparison instruction, the system also includes: In response to the selected target doctor in the doctor comparison results, the consultation page of the target doctor is displayed.

[0010] According to a second aspect of the present invention, a method for comparing medical resources is provided, applied on a server side, comprising: The system receives the target disease input, uses the patient identifier to query the knowledge base to determine the patient's basic medical characteristics, and constructs patient demand characteristics based on the patient's basic medical characteristics and the target disease. The patient's needs characteristics and the doctor's professional characteristics database in the knowledge base, as well as the feature weights, are input into the artificial intelligence model to receive and send a list of doctors associated with the target disease; The system receives preset multidimensional features and doctors from a pre-selected doctor list, inputs the preset multidimensional features and doctors from the pre-selected doctor list into an artificial intelligence model, receives and sends doctor comparison results, and the multidimensional features include one or more of the following: professional matching degree, doctor qualifications, patient satisfaction rate, consultation fee and appointment time; Receive the target doctor's identifier and send the target doctor's consultation page.

[0011] The step of inputting the preset multidimensional features and the doctors from the pre-selected doctor list into the artificial intelligence model, and receiving and sending the doctor comparison results includes: The patient's basic medical characteristics, the preset multidimensional characteristics, and the doctors in the pre-selected doctor list are input into the artificial intelligence model. The model receives and sends the doctor comparison results, which include the doctor's score on the multidimensional characteristics, the doctor's comprehensive score, and consultation suggestions.

[0012] According to a third aspect of the present invention, a medical resource comparison device is provided, applied to a patient, comprising: The association module is used to display a list of doctors associated with the target disease in response to the input target disease; The pre-selection module is used to receive pre-selection operations for multiple doctors in the doctor list, and to create and display the pre-selected doctor list; The comparison module is used to respond to the doctor's comparison instruction, receive and display the doctor comparison results under the multi-dimensional features in the doctor's comparison instruction, the multi-dimensional features including one or more of the following: professional matching degree, doctor qualifications, patient satisfaction rate, consultation fee and appointment time.

[0013] According to a fourth aspect of the present invention, a medical resource comparison device is provided, applied on a server side, comprising: The query module is used to receive the input target disease, use the patient identifier to query the knowledge base to determine the patient's basic medical characteristics, and construct the patient's demand characteristics based on the patient's basic medical characteristics and the target disease. The matching module is used to input the patient's needs characteristics, the doctor's professional characteristics library in the knowledge base, and the feature weights into the artificial intelligence model, and to receive and send a list of doctors associated with the target disease. The results module is used to receive preset multidimensional features and doctors from the pre-selected doctor list, input the preset multidimensional features and doctors from the pre-selected doctor list into the artificial intelligence model, receive and send the doctor comparison results, and the multidimensional features include one or more of the following: professional matching degree, doctor qualifications, patient satisfaction rate, consultation fee and appointment time; The target module is used to receive the identifier of the target doctor and send the consultation page of the target doctor.

[0014] According to a fifth aspect of the present invention, an electronic device for comparing medical resources is provided, comprising: One or more processors; Storage device for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors perform the methods described above.

[0015] According to a sixth aspect of the present invention, a computer-readable medium is provided having a computer program stored thereon, which, when executed by a processor, implements the method as described above.

[0016] One embodiment of the above invention has the following advantages or beneficial effects: In response to an input target disease, a list of doctors associated with the target disease is displayed; a pre-selection operation for multiple doctors in the doctor list is received, and a pre-selected doctor list is established and displayed; in response to a doctor comparison instruction, the doctor comparison results under multi-dimensional features in the doctor comparison instruction are received and displayed, the multi-dimensional features including one or more of the following: professional matching degree, doctor qualifications, patient satisfaction rate, consultation fee, and appointment time. On the patient's interface, by responding to the instructions sent by the patient, the doctor comparison results under multi-dimensional features are displayed, providing the patient with a basis for selecting doctors for online consultations, thus realizing the comparison of information from multiple doctors.

[0017] The further effects of the aforementioned unconventional alternative methods will be explained below in conjunction with specific implementation methods. Attached Figure Description

[0018] The accompanying drawings are provided to better understand the invention and are not intended to unduly limit the scope of the invention. Wherein: Figure 1 This is a comparative diagram of medical resources in existing technologies; Figure 2 This is a schematic diagram of the main process of the medical resource comparison method according to an embodiment of the present invention; Figure 3 This is a schematic diagram illustrating an application scenario of the medical resource comparison method according to an embodiment of the present invention; Figure 4 This is a flowchart illustrating the display of a pre-selected doctor list according to an embodiment of the present invention; Figure 5 This is a comparative diagram of medical resources according to an embodiment of the present invention; Figure 6 This is a schematic diagram of the process of inputting doctors from a pre-selected doctor list into an artificial intelligence model based on preset multi-dimensional features according to an embodiment of the present invention; Figure 7 This is a schematic diagram of the main process of another medical resource comparison method according to an embodiment of the present invention; Figure 8 This is a schematic diagram of the online consultation application process according to an embodiment of the present invention; Figure 9This is a schematic diagram of the main structure of a medical resource comparison device according to an embodiment of the present invention; Figure 10 This is a schematic diagram of the main structure of another medical resource comparison device according to an embodiment of the present invention; Figure 11 This is an exemplary system architecture diagram in which embodiments of the present invention can be applied; Figure 12 This is a schematic diagram of the structure of a computer system suitable for implementing terminal devices or servers of the present invention. Detailed Implementation

[0019] The following description, in conjunction with the accompanying drawings, illustrates exemplary embodiments of the present invention, including various details to aid understanding. These details should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the invention. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0020] Patients receive remote medical treatment through online platforms, and the choice of doctors is a core part of the consultation service, directly affecting the patient's medical experience and service suitability.

[0021] Figure 1 The image in the middle left shows the current online platform's doctor selection process. In practice, after a patient enters disease keywords (such as a cold), a list of related doctors is pushed based on the disease tags. It cannot proactively integrate potential patient needs such as hospital level and doctor's title. Patients need to manually select multiple filter tags to narrow down the scope.

[0022] In addition, patients can also receive automatically matched results from doctors, such as Figure 1 As shown in the middle diagram, the system directly recommends doctors matched by the doctor assistant to the patient, leaving the patient in a passive position and unable to intuitively identify whether the current doctor meets their current consultation needs. This can easily lead to a poor patient experience when choosing a doctor.

[0023] In a rapid consultation scenario, after the patient enters their disease information, such as Figure 1 As shown in the image on the right, the system first matches the patient with a corresponding department and provides recommended doctors within that department for the patient to choose from. Simultaneously, a list of renowned doctors within that department is displayed in the recommendation area below, offering patients more options.

[0024] Regardless of the method mentioned above, it is impossible to compare medical information from multiple doctors, making it difficult to meet patients' needs for comparing information from multiple doctors.

[0025] To address the difficulty in comparing information from multiple doctors, the following technical solutions from the embodiments of the present invention can be adopted.

[0026] See Figure 2 , Figure 2 This is a schematic diagram of the main process of a medical resource comparison method according to an embodiment of the present invention. Specifically, it includes the following steps: S201. In response to the input target disease, display a list of doctors associated with the target disease.

[0027] In embodiments of the present invention, patients consult doctors online through a patient-side application. For example, the patient-side application is located within a mobile application (APP) or a browser. The patient-side application interacts with the server. Figure 3 As shown, the patient-side is set up in an app on a mobile terminal. The patient-side uses the mobile terminal's screen and / or microphone to receive the patient's input. For example, the patient can input the target disease at a preset location in the mobile terminal app using the mobile terminal's keyboard or microphone. Figure 2 The patient is the primary entity responsible for executing each step in the implementation example.

[0028] After receiving the target disease input by the patient, the client sends the target disease to the server to retrieve a list of doctors associated with the target disease and displays the list. For example, the list of doctors can be displayed in descending order of relevance to the target disease.

[0029] S202: Receive the pre-selection operation for multiple doctors in the doctor list, and create and display the pre-selected doctor list.

[0030] The patient's client displays a list of doctors associated with the target disease. The patient submits a pre-selection action through the client to create and display a pre-selected doctor list. This pre-selection action includes choosing one or more doctors to add to the pre-selected doctor list from the displayed doctors page. The pre-selected doctor list contains multiple doctors, all selected by the patient.

[0031] S203. In response to the doctor comparison instruction, receive and display the doctor comparison results under the multi-dimensional features in the doctor comparison instruction. The multi-dimensional features include one or more of the following: professional matching degree, doctor qualifications, patient satisfaction rate, consultation fee and appointment time.

[0032] The pre-selected doctor list includes multiple doctors. Patients send a doctor comparison command to this list. Upon receiving the command, the patient identifies the doctors in the list based on preset multi-dimensional features, such as: professional matching degree, doctor qualifications, patient satisfaction rate, consultation fee, and appointment time. The pre-selected doctor list includes: Dr. Zhang; Dr. Li; and Dr. Wang. The professional matching degree, doctor qualifications, patient satisfaction rate, consultation fee, and appointment time for Dr. Zhang; Dr. Li; and Dr. Wang are input into the artificial intelligence model. The AI ​​model is set on a server. The doctor comparison command includes multi-dimensional features, which can be customized according to the patient's needs. For example, if the patient only focuses on professional matching degree and doctor qualifications, the multi-dimensional features are set to: professional matching degree and doctor qualifications. If the patient focuses on professional matching degree, doctor qualifications, patient satisfaction rate, and appointment time, the multi-dimensional features are set to: professional matching degree, doctor qualifications, patient satisfaction rate, and appointment time. After receiving the doctor comparison results from the AI ​​model, the patient's end displays the doctor comparison results for reference.

[0033] In one embodiment of the present invention, after displaying the doctor comparison results, the consultation page of the target doctor selected in the doctor comparison results can also be displayed in response to the target doctor.

[0034] The patient sends their selected target doctor to the client-side application. The client-side application retrieves the consultation page from the server based on the target doctor's identifier and displays the consultation page. The patient then conducts an online consultation through the consultation page displayed on the client-side application.

[0035] exist Figure 2 In this embodiment, in response to an input target disease, a list of doctors associated with the target disease is displayed; a pre-selection operation for multiple doctors in the doctor list is received, and a pre-selected doctor list is established and displayed; in response to a doctor comparison instruction, the doctor comparison results under multi-dimensional features in the doctor comparison instruction are received and displayed, the multi-dimensional features including one or more of the following: professional matching degree, doctor qualifications, patient satisfaction rate, consultation fee, and appointment time. On the patient's interface, in response to instructions sent by the patient, the doctor comparison results determined by the artificial intelligence model are displayed, providing the patient with a basis for selecting doctors for online consultations, and realizing the comparison of information from multiple doctors.

[0036] In one embodiment of the present invention, the pre-selected doctor list is the basis for realizing doctor comparison. In order to allow patients to quickly add doctors to the pre-selected doctor list and avoid repeated searching, viewing and optimization operations, the pre-selected doctor list can be established and displayed in one or more of the following ways.

[0037] Method 1: Single operation

[0038] The doctor list page displays multiple doctors, along with a brief introduction for each. For example, it might show Dr. Zhang, specializing in pediatrics; Dr. Li, specializing in internal medicine; and Dr. Wang, specializing in orthopedics.

[0039] Each doctor is identified by a doctor card. A pre-selection control is set and displayed in the upper right corner of the doctor card. For example, the pre-selection control includes an "Add to Pre-selection" button. The pre-selection button responds to the doctor pre-selection action on the doctor list page. It displays the message: "Added to the pre-selection doctor list." After the pre-selection action, the pre-selection button displays: "Added," and a pop-up message appears: "Dr. Li has been added to the pre-selection doctor list. Currently, there are 1 / 3 of the doctors in the list." The message disappears automatically after 3 seconds without obscuring the operation area. Here, 1 represents the number of doctors already selected in the pre-selection doctor list, and 3 represents the minimum number of doctors in the pre-selection doctor list.

[0040] The doctor's details page is a subpage of the doctor list page. Patients access the corresponding doctor's details page by clicking on the doctor's card in the doctor list page. The doctor's details page displays a doctor and provides detailed information about the doctor. For example: Dr. Zhang, specializing in: Pediatric Internal Medicine; 10 years of clinical experience; telephone and video consultations.

[0041] On the doctor's details page, a pre-selection control is displayed next to the doctor's icon. For example, a floating button is displayed to the right of the doctor's icon; this is the pre-selection control. The floating button scrolls with the page. If the floating button receives a pre-selection action, the pre-selected doctor list is updated synchronously to avoid duplicate additions when returning to the doctor list page.

[0042] Specifically, a preselection control is displayed on at least one of the doctor identifiers on the doctor list page and the doctor details page. In response to a preselection operation on at least one of the doctors on the doctor list page and the doctor details page, the preselection control creates a preselected doctor list and adds the doctor to the preselected doctor list. The preselection control scrolls with the page. By performing a preselection operation on the doctor list page and / or the doctor details page, doctors are added to the preselected doctor list according to the preselection operation sent by the patient.

[0043] Method 2: Batch Operation

[0044] The doctor list page displays doctor cards for multiple doctors, enabling batch pre-selection using multiple doctor identifiers. For example, batch pre-selection involves long-clicking multiple doctor cards to add multiple doctors to the pre-selection list. Long-clicked doctor cards display a colored border to enhance visual feedback and prevent duplicate selections.

[0045] The batch operation described above can add multiple doctors to the pre-selected doctor list at once, thereby increasing the speed of building the pre-selected doctor list.

[0046] In embodiments of the present invention, when the list of doctors is displayed on the patient's end, both single operations and batch operations can be performed, thereby shortening the time required to build the pre-selected doctor list by providing various operation methods.

[0047] See Figure 4 , Figure 4 This is a flowchart illustrating the display of a pre-selected doctor list according to an embodiment of the present invention. Specifically, it includes the following steps: S401. The pre-selected doctor list includes multiple information units, which display doctor information and the corresponding multi-dimensional features of the doctor.

[0048] In embodiments of the present invention, the pre-selected doctor list includes multiple information units. See also Figure 5 The left-hand image shows a pre-selected doctor list comprising three information units. Multiple information units can be displayed in a list. Each information unit displays doctor information and corresponding multi-dimensional features. Doctor information includes: doctor's name. The corresponding multi-dimensional features include department, doctor qualifications, areas of expertise, patient satisfaction rate, and consultation hours. The number of doctors is displayed below the pre-selected doctor list. Figure 5 The number 3 in the lower left image indicates that 3 doctors have been selected.

[0049] S402. A delete control is set for each information unit. In response to the operation of the delete control, a delete confirmation prompt is triggered to delete the corresponding information unit from the list of pre-selected doctors.

[0050] Each information unit has a corresponding delete control. For example: Figure 5 In the left-hand image, a delete control is placed in the upper right corner of each information unit. In response to an operation on the delete control, a deletion confirmation prompt is triggered. For example: Deletion confirmation prompt: Remove Dr. Zhang? This confirmation prompt helps prevent accidental deletion.

[0051] exist Figure 4 In this embodiment, the doctor's corresponding information is displayed in the form of information units, which improves the effectiveness of operating the information units and avoids erroneous operations.

[0052] See Figure 6 , Figure 6 This is a schematic diagram illustrating the process of inputting doctors from a pre-selected doctor list into an artificial intelligence model based on preset multi-dimensional features, according to an embodiment of the present invention. Specifically, it includes the following steps: S601. In response to the doctor comparison command, if the number of doctors in the pre-selected doctor list does not reach the preset threshold, a prompt message to add a doctor is displayed.

[0053] In online consultations, comparing doctors needs to reach a preset threshold, such as 3. This preset threshold ensures the effectiveness of comparing multiple doctors. It also ensures the pre-selected doctor list has basic diversity and comparability, avoiding meaningless or misleading conclusions due to insufficient data.

[0054] As an example, a "Start Comparison" button is placed at the bottom of the doctor comparison page. This button responds to the doctor's comparison command. The pre-selected doctor list includes Dr. Li, Dr. Zhang, and Dr. Wang. If the number of pre-selected doctors exceeds a preset threshold, the "Start Comparison" button is highlighted and clickable. If the pre-selected doctor list includes Dr. Li and the number of pre-selected doctors is less than the preset threshold, the "Start Comparison" button is highlighted in gray and is not clickable. A prompt to add a doctor is displayed. This prompt guides patients to add doctor information and avoids confusion.

[0055] S602. Display a preselection control at the doctor's identifier on the doctor list page or doctor details page. The preselection control, in response to a doctor addition instruction, adds the doctor to the preselected doctor list to execute the doctor comparison instruction.

[0056] To add a doctor to the pre-selected doctor list, the pre-selection control responds to a doctor addition instruction. Once the pre-selected doctor list meets a preset threshold, a doctor comparison instruction can be executed to perform doctor comparison. For example, the doctor identifiers from the pre-selected doctor list, along with their corresponding preset multi-dimensional features, are input into the artificial intelligence model. These preset multi-dimensional features are used for doctor comparison.

[0057] exist Figure 6 In one embodiment, adding doctor prompts to remind patients enables effective comparison among multiple doctors.

[0058] In one embodiment of the present invention, after receiving the doctor comparison results from the pre-selected doctor list, the doctor comparison results are displayed on the patient's end. The doctor comparison results include the doctor's scores on multi-dimensional features, the doctor's overall score, and consultation suggestions.

[0059] Multidimensional features can be identified in the table, which also displays the scores for each doctor in the pre-selected doctor list based on these features. For example, multidimensional features might include: professional suitability, doctor qualifications, patient satisfaction rate, consultation fees, and appointment time. By analyzing the doctors' scores on these multidimensional features, the table reveals their strengths and weaknesses across different dimensions.

[0060] The physician's overall score is used for comprehensive evaluation. Different colors are used to display the physician's overall score. For example, red indicates a score of 90 or above; yellow indicates a score of 70 to 89; and gray indicates a score below 70.

[0061] The consultation suggestions are determined using an artificial intelligence model based on the patient's basic medical characteristics, multidimensional feature scores, and the doctor's comprehensive score. The patient's basic medical characteristics are stored in a knowledge base on the server. Based on the target disease, the patient's basic medical characteristics, multidimensional feature scores, and the doctor's comprehensive score are input into the artificial intelligence model to generate consultation suggestions tailored to the patient.

[0062] The AI ​​model integrates scores based on multiple dimensions, including professional matching, doctor qualifications, patient satisfaction rate, consultation fees, and appointment time, along with the doctor's overall score, transforming abstract data into easily understandable visualizations. For example, a consultation suggestion might include: "Given a history of hypertension, it is recommended to provide the doctor with blood pressure records from the past week." Furthermore, consultation suggestions can also include the strengths and weaknesses of multiple doctors. For instance, "Dr. Zhang has a high matching score but late appointment times; Dr. Li can see you immediately with lower treatment costs."

[0063] See Figure 7 , Figure 7 This is a schematic diagram of the main flow of another medical resource comparison method according to an embodiment of the present invention. It is applied to the server side. Specifically, it includes the following steps: S701. Receive the input target disease, use the patient identifier to query the knowledge base to determine the patient's basic medical characteristics, and construct the patient's demand characteristics based on the patient's basic medical characteristics and the target disease.

[0064] Figure 7 The server is the primary entity executing each step. The server sets up a knowledge base and an artificial intelligence model. The server receives the target disease sent by the patient. Considering the correlation between diseases, the knowledge base stores the patient's basic medical characteristics; therefore, the patient's basic medical characteristics are determined by querying the knowledge base using the patient's identifier. For example, the patient's basic medical characteristics include: gender; age; underlying diseases; and medication history.

[0065] Patient needs profiles are constructed based on the patient's basic medical characteristics and the target disease. As an example, patient needs profiles include: the ICD-10 code for the target disease; core symptoms; and treatment preferences. ICD-10 is an internationally unified disease classification standard developed by the World Health Organization (WHO), officially known as the International Statistical Classification of Diseases and Related Health Problems. It systematically codes diseases based on characteristics such as etiology, pathology, and clinical manifestations. Patient needs profiles represent the patient's unique characteristics, enabling the targeted identification of appropriate physicians.

[0066] S702. Input the patient's needs characteristics and the doctor's professional characteristics database in the knowledge base, as well as the feature weights, into the artificial intelligence model, and receive and send a list of doctors associated with the target disease.

[0067] The knowledge base stores a database of doctors' professional characteristics. Corresponding professional characteristics are established for each doctor. As an example, these characteristics include: area of ​​expertise, diseases of expertise, professional title, treatment fees, patient reviews, and consultation hours.

[0068] Feature weights represent the degree of importance of a factor or indicator relative to a thing. Unlike general proportions, they do not only reflect the percentage of a factor or indicator, but emphasize the relative importance of the factor or indicator, tending to indicate contribution or importance.

[0069] To reflect the impact of different doctor characteristics on the target disease, feature weights can be pre-defined. For example: core disease matching, weight 40%; symptom matching, weight 25%; qualification and experience matching, weight 15%; price matching, weight 10%; positive review rate matching, weight 10%.

[0070] The system inputs patient needs characteristics, a database of physician professional characteristics from a knowledge base, and feature weights into an AI model. It then receives and sends a list of physicians associated with the target disease. This initial list serves as a preliminary selection, laying a precise data foundation for subsequent multi-dimensional physician comparisons.

[0071] S703: Receive preset multidimensional features and doctors from the pre-selected doctor list, input the preset multidimensional features and doctors from the pre-selected doctor list into the artificial intelligence model, receive and send the doctor comparison results. The multidimensional features include one or more of the following: professional matching degree, doctor qualifications, patient satisfaction rate, consultation fee and appointment time.

[0072] The server receives preset multidimensional features and a list of pre-selected doctors from the patient's computer. The number of doctors must be greater than or equal to a preset threshold. The server then inputs these preset multidimensional features and the doctors from the pre-selected doctor list into the artificial intelligence model, and receives and sends the doctor comparison results.

[0073] In one embodiment of the present invention, to improve the relevance of doctor comparison results, the patient's basic medical characteristics can be output to the artificial intelligence model. This involves inputting the patient's basic medical characteristics, preset multi-dimensional characteristics, and doctors from a pre-selected doctor list into the AI ​​model. The input of the patient's basic medical characteristics allows the doctor comparison process to incorporate these characteristics. For example, if the patient's basic medical characteristics include a history of heart disease, the doctor comparison results may include recommendations for doctors with a history of heart disease.

[0074] The server receives and sends the doctor comparison results, which include the doctor's scores on multidimensional features, the doctor's overall score, and consultation suggestions.

[0075] S704: Receive the target doctor's identifier and send the target doctor's consultation page.

[0076] When the server receives the identifier of the target doctor sent by the patient, indicating that the patient has identified a target doctor, it sends the target doctor's consultation page to the patient's device so that the consultation page can be displayed on the patient's device.

[0077] exist Figure 7 In one embodiment, the server uses a knowledge base and an artificial intelligence model to interact with the patient and compare information from multiple doctors.

[0078] See Figure 8 , Figure 8 This is a schematic diagram of the online consultation application process according to an embodiment of the present invention.

[0079] S801, Patient enters target disease.

[0080] Patients input their target disease via voice on the patient terminal.

[0081] S802, Output a list of doctors associated with the target disease.

[0082] The server uses an artificial intelligence model to obtain a list of doctors associated with patients and target diseases.

[0083] S803. Select a doctor and add them to the list of pre-selected doctors.

[0084] During the browsing process on the patient's device, the patient adds three doctors to the pre-selected doctor list, such as... Figure 5 As shown in the middle left image. Patients can also... Figure 5 In the search box at the top of the left-hand image, search for relevant doctors based on their physician or specific department and compare their results.

[0085] The list of pre-selected doctors displays the doctor's name, department, title, areas of expertise, patient reviews, and available time for further reference. After selecting a doctor, patients can click the "Compare" button below to receive suggestions from the AI ​​model.

[0086] S804. Determine if the number of doctors in the pre-selected doctor list is greater than or equal to 3.

[0087] The preset quantity threshold is 3. If the number of doctors in the doctor list is greater than or equal to 3, execute S805; otherwise, select a doctor again and add it to the pre-selected doctor list.

[0088] S805, Start the comparison.

[0089] In response to the doctor comparison command, the system inputs doctors from the pre-selected doctor list into the artificial intelligence model based on preset multi-dimensional features. The doctor comparison command includes multi-dimensional features: professional matching degree, doctor qualifications, patient satisfaction rate, consultation fee and appointment time.

[0090] S806: Display multi-dimensional comparison results.

[0091] The patient's end receives and displays the doctor comparison results. It filters the doctors who best meet the patient's criteria across various dimensions, displays the doctor's core strengths on the patient's page, and lists the doctor's comparison details. For example: Figure 5 As shown in the middle figure.

[0092] S807, Assisting patients in selecting their target doctor.

[0093] Patients can choose a specific doctor based on the specific recommendations of the artificial intelligence model. For example... Figure 5 As shown in the middle right image, after the patient completes the operation on the doctor selection interface, clicks to select Dr. Li and triggers the command to return to the pre-selection list, they will enter the detailed information display and follow-up service guidance stage.

[0094] Show full service details: basic information (name, title, area of ​​expertise), service price (e.g., "text and image consultation 198 yuan", "video consultation 328 yuan"), timeliness ("text and image consultation will be responded to within 24 hours"), and customer rating.

[0095] A "Go to Consultation" button is located below the doctor's card. Clicking "Go to Consultation" will redirect you to the payment page, displaying the order details. After payment is completed, a "Payment Successful" page will pop up, and an SMS notification will be sent simultaneously. Patients can click "Enter Consultation Now" or receive a pop-up reminder 10 minutes before the appointment.

[0096] In the above embodiments, by comparing doctor information from multiple dimensions, patients can intuitively obtain and compare core information such as the target doctor's qualification level, number of patients seen, service price, positive review rate, and diseases they are good at on the same interface without switching pages. This significantly reduces the cost for patients to integrate fragmented information, significantly improves the efficiency of doctor selection decisions, and assists patients in making reasonable and appropriate doctor selection judgments based on clear comparison content, combined with their own budget, disease complexity, and timeliness of medical treatment needs. This reduces the bias in doctor selection caused by subjective judgment, thereby improving patients' online consultation experience and treatment expectations, and ultimately effectively improving user satisfaction.

[0097] See Figure 9 , Figure 9 This is a schematic diagram of the main structure of a medical resource comparison device according to an embodiment of the present invention. The medical resource comparison device is applied to the patient end and specifically includes: The association module 901 is used to display a list of doctors associated with the target disease in response to the input target disease; The pre-selection module 902 is used to receive pre-selection operations for multiple doctors in the doctor list, and to create and display the pre-selected doctor list; The comparison module 903 is used to respond to the doctor's comparison instruction, receive and display the doctor comparison results under the multi-dimensional features in the doctor's comparison instruction, the multi-dimensional features including one or more of the following: professional matching degree, doctor qualifications, patient satisfaction rate, consultation fee and appointment time; The consultation module 904 is used to display the consultation page of the target doctor selected in the doctor comparison results.

[0098] In one embodiment of the present invention, a preselection module 902 is configured to display a preselection control on at least one of the doctor identifiers in the doctor list page and the doctor details page. The preselection control, in response to a preselection operation on at least one of the doctors in the doctor list page and the doctor details page, establishes the preselected doctor list and adds the doctor to the preselected doctor list. The preselection control scrolls with the page. And / or, In response to a batch pre-selection operation of multiple doctor identifiers on the doctor list page, the pre-selected doctor list is created and multiple doctors are added to the pre-selected doctor list.

[0099] In one embodiment of the present invention, a pre-selection module 902 is used to enable the pre-selected doctor list to include multiple information units, wherein the information units display doctor information and multi-dimensional features corresponding to the doctor; The information unit is equipped with a corresponding deletion control. In response to the operation of the deletion control, a deletion confirmation prompt is triggered to delete the corresponding information unit from the list of pre-selected doctors.

[0100] In one embodiment of the present invention, the comparison module 903 is used to display a prompt message to add a doctor in response to a doctor's comparison instruction, when the number of doctors in the pre-selected doctor list does not reach a preset number threshold. A pre-selection control is displayed at the doctor's identifier on the doctor list page or doctor details page. The pre-selection control, in response to a doctor addition instruction, adds the doctor to the pre-selected doctor list to execute the doctor comparison instruction.

[0101] In one embodiment of the present invention, a comparison module 903 is used to identify the multidimensional features in a table, and to display the doctor's rating of the multidimensional features in the table; The doctor's overall score is indicated and displayed using different colors; The consultation suggestions are displayed and are determined using an artificial intelligence model based on the patient's basic medical characteristics, the scores of the multidimensional characteristics, and the doctor's comprehensive score.

[0102] See Figure 10 , Figure 10This is a schematic diagram of the main structure of another medical resource comparison device according to an embodiment of the present invention. The medical resource comparison device is applied to the server side and specifically includes: The query module 1001 is used to receive the input target disease, use the patient identifier to query the knowledge base to determine the patient's basic medical characteristics, and construct the patient's demand characteristics based on the patient's basic medical characteristics and the target disease. The matching module 1002 is used to input the patient demand characteristics and the doctor professional characteristic library in the knowledge base, as well as the feature weights, into the artificial intelligence model, and to receive and send a list of doctors associated with the target disease. The result module 1003 is used to receive preset multidimensional features and doctors from the pre-selected doctor list, input the preset multidimensional features and doctors from the pre-selected doctor list into the artificial intelligence model, receive and send the doctor comparison results, and the multidimensional features include one or more of the following: professional matching degree, doctor qualifications, patient satisfaction rate, consultation fee and appointment time. The target module 1004 is used to receive the identifier of the target doctor and send the consultation page of the target doctor.

[0103] In one embodiment of the present invention, the result module 1003 is used to input the patient's basic medical characteristics, the preset multidimensional characteristics and the doctors in the pre-selected doctor list into the artificial intelligence model, receive and send the doctor comparison results, the doctor comparison results including the doctor's score on the multidimensional characteristics, the doctor's comprehensive score and consultation suggestions.

[0104] Figure 11 An exemplary system architecture 1100 is shown, in which the medical resource comparison method or medical resource comparison apparatus of embodiments of the present invention can be applied.

[0105] like Figure 11 As shown, system architecture 1100 may include terminal devices 1101, 1102, and 1103, network 1104, and server 1105. Network 1104 is used as a medium to provide communication links between terminal devices 1101, 1102, and 1103 and server 1105. Network 1104 may include various connection types, such as wired or wireless communication links or fiber optic cables, etc.

[0106] Users can use terminal devices 1101, 1102, and 1103 to interact with server 1105 via network 1104 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 1101, 1102, and 1103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social media platform software, etc. (for example only).

[0107] Terminal devices 1101, 1102, and 1103 can be various electronic devices with displays and web browsing capabilities, including but not limited to smartphones, tablets, laptops, and desktop computers.

[0108] Server 1105 can be a server that provides various services, such as a backend management server that supports shopping websites browsed by users using terminal devices 1101, 1102, and 1103 (for example only). The backend management server can analyze and process data such as received product information query requests, and feed back the processing results (such as target push information, product information - for example only) to the terminal devices.

[0109] It should be noted that the medical resource comparison method provided in this embodiment of the invention is generally executed by server 1105, and correspondingly, the medical resource comparison device is generally set in server 1105.

[0110] It should be understood that Figure 11 The number of terminal devices, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be included.

[0111] The following is for reference. Figure 12 It shows a schematic diagram of the structure of a computer system 1200 suitable for implementing a terminal device of the present invention. Figure 12 The terminal device shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0112] like Figure 12 As shown, the computer system 1200 includes a central processing unit (CPU) 1201, which can perform various appropriate actions and processes based on programs stored in read-only memory (ROM) 1202 or programs loaded from storage section 1208 into random access memory (RAM) 1203. The RAM 1203 also stores various programs and data required for the operation of the system 1200. The CPU 1201, ROM 1202, and RAM 1203 are interconnected via a bus 1204. An input / output (I / O) interface 1205 is also connected to the bus 1204.

[0113] The following components are connected to I / O interface 1205: an input section 1206 including a keyboard, mouse, etc.; an output section 1207 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 1208 including a hard disk, etc.; and a communication section 1209 including a network interface card such as a LAN card, modem, etc. The communication section 1209 performs communication processing via a network such as the Internet. A drive 1210 is also connected to I / O interface 1205 as needed. Removable media 1211, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 1210 as needed so that computer programs read from them can be installed into storage section 1208 as needed.

[0114] In particular, according to the embodiments disclosed in this invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 1209, and / or installed from removable medium 1211. When the computer program is executed by central processing unit (CPU) 1201, it performs the functions defined above in the system of this invention.

[0115] It should be noted that the computer-readable medium shown in this invention can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-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 thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this invention, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media can also be any computer-readable medium other than computer-readable storage media, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0116] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0117] The modules described in the embodiments of the present invention can be implemented in software or hardware. The described modules can also be housed in a processor; for example, a processor can be described as including an association module, a pre-selection module, a comparison module, a consultation module, a query module, a matching module, a result module, and a target module. The names of these modules do not necessarily limit the module itself; for example, the association module can also be described as "for displaying a list of doctors associated with the target disease in response to an input target disease."

[0118] In another aspect, the present invention also provides a computer-readable medium, which may be included in the device described in the above embodiments; or it may exist independently and not assembled into the device. The computer-readable medium carries one or more programs, which, when executed by the device, cause the device to include: In response to the input of a target disease, a list of doctors associated with the target disease is displayed; Receive pre-selection operations for multiple doctors in the doctor list, and create and display the pre-selected doctor list; In response to a doctor comparison instruction, the system receives and displays the doctor comparison results under the multi-dimensional features in the doctor comparison instruction. The multi-dimensional features include one or more of the following: professional matching degree, doctor qualifications, patient satisfaction rate, consultation fee, and appointment time.

[0119] According to the technical solution of this invention, in response to an input target disease, a list of doctors associated with the target disease is displayed; a pre-selection operation for multiple doctors in the doctor list is received, and a pre-selected doctor list is established and displayed; in response to a doctor comparison instruction, the doctor comparison results under multi-dimensional features in the doctor comparison instruction are received and displayed, the multi-dimensional features including one or more of the following: professional matching degree, doctor qualifications, patient satisfaction rate, consultation fee, and appointment time. On the patient's interface, by responding to the instructions sent by the patient, the doctor comparison results determined by the artificial intelligence model are displayed, providing the patient with a basis for selecting doctors for online consultation, thus realizing the comparison of information from multiple doctors.

[0120] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can occur depending on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention. It should be noted that the acquisition, storage, and application of user personal information involved in the technical solutions of this disclosure comply with relevant laws and regulations and do not violate public order and good morals.

Claims

1. A method for comparing medical resources, characterized in that, For patient use, including: In response to the input of a target disease, a list of doctors associated with the target disease is displayed; Receive pre-selection operations for multiple doctors in the doctor list, and create and display the pre-selected doctor list; In response to a doctor comparison instruction, the system receives and displays the doctor comparison results under the multi-dimensional features in the doctor comparison instruction. The multi-dimensional features include one or more of the following: professional matching degree, doctor qualifications, patient satisfaction rate, consultation fee, and appointment time.

2. The method for comparing medical resources according to claim 1, characterized in that, The step of receiving a pre-selection operation for multiple doctors in the doctor list, and establishing and displaying the pre-selected doctor list, includes: A preselection control is displayed in at least one of the doctor identifiers on the doctor list page and the doctor details page. The preselection control is in response to a preselection operation on at least one of the doctors on the doctor list page and the doctor details page, to create the preselected doctor list and add the doctor to the preselected doctor list. The preselection control scrolls with the page. And / or, In response to a batch pre-selection operation of multiple doctor identifiers on the doctor list page, the pre-selected doctor list is created and multiple doctors are added to the pre-selected doctor list.

3. The method for comparing medical resources according to claim 1, characterized in that, The list of pre-selected doctors displayed includes: The pre-selected doctor list includes multiple information units, which display doctor information and corresponding multi-dimensional features of the doctor. The information unit is equipped with a corresponding deletion control. In response to the operation of the deletion control, a deletion confirmation prompt is triggered to delete the corresponding information unit from the list of pre-selected doctors.

4. The method for comparing medical resources according to claim 1, characterized in that, The response to the doctor's comparison instruction includes: In response to a doctor comparison command, if the number of doctors in the pre-selected doctor list does not reach a preset threshold, a prompt to add a doctor will be displayed. A pre-selection control is displayed at the doctor's identifier on the doctor list page or doctor details page. The pre-selection control, in response to a doctor addition instruction, adds the doctor to the pre-selected doctor list to execute the doctor comparison instruction.

5. The method for comparing medical resources according to claim 1, characterized in that, The doctor comparison results displayed under the multidimensional features in the doctor comparison instruction include one or more of the following: The multidimensional features are identified in a table, and the doctor's scores on the multidimensional features are displayed in the table; The doctor's overall score is indicated and displayed using different colors; The consultation suggestions are displayed and are determined using an artificial intelligence model based on the patient's basic medical characteristics, the scores of the multidimensional characteristics, and the doctor's comprehensive score. And / or, Following the display of the doctor comparison results under the multidimensional features in the doctor comparison instruction, the system also includes: In response to the selected target doctor in the doctor comparison results, the consultation page of the target doctor is displayed.

6. A method for comparing medical resources, characterized in that, Applied to the server side, including: The system receives the target disease input, uses the patient identifier to query the knowledge base to determine the patient's basic medical characteristics, and constructs patient demand characteristics based on the patient's basic medical characteristics and the target disease. The patient's needs characteristics and the doctor's professional characteristics database in the knowledge base, as well as the feature weights, are input into the artificial intelligence model to receive and send a list of doctors associated with the target disease; The system receives preset multidimensional features and doctors from a pre-selected doctor list, inputs these features into an artificial intelligence model, receives and sends doctor comparison results, and the multidimensional features include one or more of the following: professional matching degree, doctor qualifications, patient satisfaction rate, consultation fee, and appointment time; it also receives the identifier of the target doctor and sends the consultation page of the target doctor.

7. The method for comparing medical resources according to claim 6, characterized in that, The step of inputting the preset multidimensional features and the doctors from the pre-selected doctor list into the artificial intelligence model, and receiving and sending the doctor comparison results includes: The patient's basic medical characteristics, the preset multidimensional characteristics, and the doctors in the pre-selected doctor list are input into the artificial intelligence model. The model receives and sends the doctor comparison results, which include the doctor's score on the multidimensional characteristics, the doctor's comprehensive score, and consultation suggestions.

8. A medical resource comparison device, characterized in that, For patient use, including: The association module is used to display a list of doctors associated with the target disease in response to the input target disease; The pre-selection module is used to receive pre-selection operations for multiple doctors in the doctor list, and to create and display the pre-selected doctor list; The comparison module is used to respond to the doctor's comparison instruction, receive and display the doctor comparison results under the multi-dimensional features in the doctor's comparison instruction, the multi-dimensional features including one or more of the following: professional matching degree, doctor qualifications, patient satisfaction rate, consultation fee and appointment time.

9. A medical resource comparison device, characterized in that, Applied to the server side, including: The query module is used to receive the input target disease, use the patient identifier to query the knowledge base to determine the patient's basic medical characteristics, and construct the patient's demand characteristics based on the patient's basic medical characteristics and the target disease. The matching module is used to input the patient's needs characteristics, the doctor's professional characteristics library in the knowledge base, and the feature weights into the artificial intelligence model, and to receive and send a list of doctors associated with the target disease. The results module is used to receive preset multidimensional features and doctors from the pre-selected doctor list, input the preset multidimensional features and doctors from the pre-selected doctor list into the artificial intelligence model, receive and send the doctor comparison results, and the multidimensional features include one or more of the following: professional matching degree, doctor qualifications, patient satisfaction rate, consultation fee and appointment time; The target module is used to receive the identifier of the target doctor and send the consultation page of the target doctor.

10. An electronic device for comparing medical resources, characterized in that, include: One or more processors; Storage device for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any one of claims 1-7.

11. A computer-readable medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1-7.

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