CN112582060A - Multimedia auxiliary inquiry system for depression preliminary screening - Google Patents
Multimedia auxiliary inquiry system for depression preliminary screening Download PDFInfo
- Publication number
- CN112582060A CN112582060A CN202011465603.0A CN202011465603A CN112582060A CN 112582060 A CN112582060 A CN 112582060A CN 202011465603 A CN202011465603 A CN 202011465603A CN 112582060 A CN112582060 A CN 112582060A
- Authority
- CN
- China
- Prior art keywords
- inquiry
- module
- depression
- data
- target user
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/33—Querying
- G06F16/332—Query formulation
- G06F16/3329—Natural language query formulation or dialogue systems
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/33—Querying
- G06F16/3331—Query processing
- G06F16/334—Query execution
- G06F16/3343—Query execution using phonetics
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/40—Information retrieval; Database structures therefor; File system structures therefor of multimedia data, e.g. slideshows comprising image and additional audio data
- G06F16/43—Querying
- G06F16/432—Query formulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/40—Information retrieval; Database structures therefor; File system structures therefor of multimedia data, e.g. slideshows comprising image and additional audio data
- G06F16/43—Querying
- G06F16/432—Query formulation
- G06F16/433—Query formulation using audio data
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/70—Information retrieval; Database structures therefor; File system structures therefor of video data
- G06F16/73—Querying
- G06F16/732—Query formulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/045—Combinations of networks
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
- G16H10/20—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for electronic clinical trials or questionnaires
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Data Mining & Analysis (AREA)
- General Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Databases & Information Systems (AREA)
- Mathematical Physics (AREA)
- General Physics & Mathematics (AREA)
- Computational Linguistics (AREA)
- Multimedia (AREA)
- General Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Biomedical Technology (AREA)
- Public Health (AREA)
- Primary Health Care (AREA)
- Epidemiology (AREA)
- Artificial Intelligence (AREA)
- Biophysics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Pathology (AREA)
- Software Systems (AREA)
- Evolutionary Computation (AREA)
- Computing Systems (AREA)
- Molecular Biology (AREA)
- Human Computer Interaction (AREA)
- Acoustics & Sound (AREA)
- Audiology, Speech & Language Pathology (AREA)
- Medical Treatment And Welfare Office Work (AREA)
Abstract
The invention discloses a multimedia auxiliary inquiry system for preliminary screening of depression, which comprises a user login module, an inquiry module and a data processing module which are sequentially connected; the user login module is used for completing user login according to the identity information of the target user; the inquiry module is used for performing inquiry interaction with the target user according to preset inquiry content after the target user finishes logging in to obtain corresponding inquiry data; and the data processing module is used for determining a corresponding depression inquiry result according to the inquiry data. The invention can assist in identifying possible depression patients, reduce the workload of medical staff and improve the depression diagnosis efficiency.
Description
Technical Field
The invention relates to the technical field of auxiliary diagnosis and treatment, in particular to a multimedia auxiliary inquiry system for the preliminary screening of depression.
Background
The global prevalence of depression (MDD) is as high as 5% -12%, with 15% of patients self-killing. The prevalence rate of depression in China is 6.1%, and the proportion of total disease burden of depression in China in 2020 is increased to 7.3% according to the estimation of the Chinese disease prevention and control center. Depression has become a major public health problem with urgent clinical research needs.
However, the detection and prevention of depression face many problems, such as low identification accuracy of depression, lack of medical resources, lack of trained health care personnel, and the like, so that the introduction of artificial intelligence related technology is urgently needed to improve the identification accuracy of depression, make up for the vacancy of doctors in the medical industry, and improve the detection and prediction efficiency of depression. In addition, in the current depression diagnosis and treatment process, a large amount of repeated inquiry work based on scales exists, the artificial intelligence technology can be adopted to release human experts from physical labor, more energy is put on judgment of complex clues, and more patients are cared for in the same time.
Disclosure of Invention
The invention provides a multimedia auxiliary inquiry system for a preliminary screening of depression, which is used for assisting in identifying possible depression patients, reducing the workload of medical staff and improving the depression diagnosis efficiency.
The invention provides a multimedia auxiliary inquiry system for a depression primary screen, which comprises: the system comprises a user login module, an inquiry module and a data processing module which are connected in sequence;
the user login module is used for completing user login according to the identity information of the target user;
the inquiry module is used for performing inquiry interaction with the target user according to preset inquiry content after the target user finishes logging in to obtain corresponding inquiry data;
and the data processing module is used for determining a corresponding depression inquiry result according to the inquiry data.
Optionally, the system further comprises an auxiliary result presentation module, configured to present the inquiry result and the corresponding visit suggestion to the user according to the inquiry result.
Optionally, the interrogation module includes at least one of:
the text inquiry module is used for performing inquiry interaction with the target user according to text data corresponding to the standardized questions;
the voice inquiry module is used for performing inquiry interaction with the target user according to the voice data corresponding to the standardized questions;
and the video inquiry module is used for performing inquiry interaction with the target user according to the video data corresponding to the standardized questions.
Optionally, the voice inquiry module is further configured to perform voice synthesis according to the standardized question to obtain a voice packet of a corresponding virtual doctor;
the video inquiry module is also used for carrying out video synthesis according to the standardized questions so as to obtain corresponding virtual images.
Optionally, the system further includes a questionnaire module, configured to present a PHQ9 questionnaire to the target user, and acquire questionnaire information of the target user.
Optionally, the system further comprises a data storage module, configured to store the PHQ9 questionnaire, questionnaire information, questionnaire content, and questionnaire data.
Optionally, the data processing module includes:
the prediction unit is used for predicting based on the inquiry data through a preset neural network model so as to obtain prediction data;
and the data operation unit determines a corresponding depression inquiry result according to the prediction data, the questionnaire information and the corresponding weight value in English.
Optionally, the system further comprises a question and answer request module, configured to obtain a question corresponding to the inquiry content from a database, and send a question and answer request to the target user.
Optionally, a science popularization module is further included, and is used for pushing depression science popularization information to the target user.
The embodiment of the invention is used for performing inquiry interaction with a target user according to preset inquiry content after the target user finishes logging in through the inquiry module to obtain corresponding inquiry data; the data processing module is used for determining a corresponding depression inquiry result according to the inquiry data, and the method can assist in identifying possible depression patients, reduce the workload of medical staff and improve the depression diagnosis efficiency.
The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:
FIG. 1 is a schematic structural diagram of an embodiment of the present invention;
FIG. 2 is a schematic structural diagram of an interrogation module according to an embodiment of the present invention;
FIG. 3 is a flow chart of an embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
The embodiment of the invention provides a multimedia auxiliary inquiry system for a primary screening of depression, which comprises the following components in percentage by weight as shown in figure 1: the system comprises a user login module, an inquiry module and a data processing module which are connected in sequence;
the user login module is used for completing user login according to the identity information of the target user;
the inquiry module is used for performing inquiry interaction with the target user according to preset inquiry content after the target user finishes logging in to obtain corresponding inquiry data;
and the data processing module is used for determining a corresponding depression inquiry result according to the inquiry data.
Specifically, as shown in fig. 1, in this embodiment, the user logs in the authentication module, and can successfully log in by identifying information such as a user name and a password of the target user. Meanwhile, the data storage module is convenient for classifying and storing the three multimedia information of voice, text and video of the target user according to the basic information of the target user.
And the inquiry module performs inquiry interaction with the target user according to preset inquiry contents to obtain corresponding inquiry data after the target user logs in, wherein the preset inquiry contents can specifically include contents such as voice, text and video corresponding to standardized questions, and the preset inquiry contents perform inquiry interaction with the target user to obtain corresponding inquiry data.
The data processing module determines whether the target user is a depressive patient based on the obtained inquiry data.
The embodiment of the invention is used for performing inquiry interaction with a target user according to preset inquiry content after the target user finishes logging in through the inquiry module to obtain corresponding inquiry data; the data processing module is used for determining a corresponding depression inquiry result according to the inquiry data, and the embodiment can assist in identifying possible depression patients, reduce the workload of medical staff and improve the depression diagnosis efficiency.
Optionally, the system further comprises an auxiliary result presentation module, configured to present the inquiry result and the corresponding visit suggestion to the user according to the inquiry result.
Specifically, after the results of the depression inquiry are obtained, the auxiliary diagnosis result presentation module visually presents the results obtained by the data processing module and gives medical advice.
Optionally, the interrogation module includes at least one of:
the text inquiry module is used for performing inquiry interaction with the target user according to text data corresponding to the standardized questions;
the voice inquiry module is used for performing inquiry interaction with the target user according to the voice data corresponding to the standardized questions;
and the video inquiry module is used for performing inquiry interaction with the target user according to the video data corresponding to the standardized questions.
Optionally, the voice inquiry module is further configured to perform voice synthesis according to the standardized question to obtain a voice packet of a corresponding virtual doctor;
the video inquiry module is also used for carrying out video synthesis according to the standardized questions so as to obtain corresponding virtual images.
In some embodiments, in this embodiment, as shown in fig. 2 and 3, the interrogation module may include one of the following:
the system comprises a text inquiry module, a voice inquiry module and a video inquiry module. After receiving the question-answer request sent by the question-answer request module, the inquiry module inquires the user about the question in the form of voice conversation, text conversation or video conversation so as to obtain the voice information, text information and video information corresponding to the user response. For example, the reply text information of the target user is obtained through text interaction, the reply voice information of the target user is obtained through voice interaction, and the reply video information of the target user is obtained through video interaction, which of course may be a combination of the above manners without limitation.
Specifically, in the text inquiry module, standardized questions in the database can be inquired in a text mode, the target user replies to the virtual doctor in a text or voice mode, and text information or voice information of the target user is collected in the process that the target user replies to the virtual doctor.
The voice inquiry unit is connected with the database, synthesizes the standardized questions in the database into the sound of different virtual doctors by a voice synthesis method, inquires the questions of the user in a voice mode, and collects the voice information or/and text information of the target user in the process of inquiring the questions. Before the virtual doctors ask questions, the target users can select virtual doctors with different sounds according to own preferences.
The video inquiry module realizes the face-to-face interactive communication and intelligent inquiry and answer between a virtual doctor and a target user by utilizing the virtual image technology and combining key technologies such as voice recognition, semantic understanding, voice synthesis, virtual image driving and the like, and records the video information of the target user in the interactive communication process.
The specific standardization problem may be as shown in table 1.
TABLE 1 standardization issue
Optionally, the system further comprises a question and answer request module, configured to obtain a question corresponding to the inquiry content from a database, and send a question and answer request to the target user.
Optionally, the system further includes a questionnaire module, configured to present a PHQ9 questionnaire to the target user, and acquire questionnaire information of the target user.
Optionally, the system further comprises a data storage module, configured to store the PHQ9 questionnaire, questionnaire information, questionnaire content, and questionnaire data.
In some embodiments, as shown in fig. 1, a questionnaire module may be further included, and may collect information of the user's reply PHQ9 in the form of questionnaire replies and store the collected information in the data storage module, so that the data processing module may give a result of the auxiliary diagnosis according to the questionnaire result. And the data storage module is used for storing user login and authentication information, PHQ9 questionnaire reply information, questionnaire evaluation information, voice inquiry content, text inquiry content, video inquiry content and corresponding inquiry data of the user in the inquiry process.
Optionally, the data processing module includes:
the prediction unit is used for predicting based on the inquiry data through a preset neural network model so as to obtain prediction data;
and the data operation unit determines a corresponding depression inquiry result according to the prediction data, the questionnaire information and the corresponding weight value in English.
In some embodiments, the data processing module adopts a deep neural network model to model voice information, text information and video information in the data storage module, and predicts whether the tested user has depression by using the deep neural network model which is modeled in advance. Then, using the PHQ9 questionnaire reply information obtained by the data storage module, it is determined whether the user has depression. And finally, determining whether the detected user belongs to the depression user or not according to the prediction result of the deep neural network model and the corresponding weight value thereof, and the PHQ9 questionnaire result and the weighting result of the corresponding weight value thereof.
Optionally, a science popularization module is further included, and is used for pushing depression science popularization information to the target user.
In some embodiments, after the diagnosis result is presented, the science popularization module pushes relevant science popularization information such as the pathogenesis of the depression and intervention measures of the depression to the user, so that the user can know the relevant knowledge of the depression conveniently.
The multimedia auxiliary inquiry system for the preliminary screening of the depression can record basic information, voice information, text information and video information of staff of depression patients on line, can assist in judging whether the user suffers from the depression or not through the voice, the text information and the video information of the user, and can improve the working efficiency of doctors.
The multimedia auxiliary inquiry system for the preliminary screening of the depression in the embodiment queries the user in a voice conversation, text conversation or video conversation mode, and is efficient and convenient.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
While the present invention has been described with reference to the embodiments shown in the drawings, the present invention is not limited to the embodiments, which are illustrative and not restrictive, and it will be apparent to those skilled in the art that various changes and modifications can be made therein without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (9)
1. A multimedia auxiliary inquiry system facing to depression preliminary screening is characterized by comprising: the system comprises a user login module, an inquiry module and a data processing module which are connected in sequence;
the user login module is used for completing user login according to the identity information of the target user;
the inquiry module is used for performing inquiry interaction with the target user according to preset inquiry content after the target user finishes logging in to obtain corresponding inquiry data;
and the data processing module is used for determining a corresponding depression inquiry result according to the inquiry data.
2. The preliminary screening for depression multimedia-assisted interrogation system of claim 1, further comprising an assisted outcome presentation module for presenting the interrogation outcomes and corresponding visit recommendations to the user in accordance with the presentation.
3. The preliminary screening for depression multimedia-assisted interrogation system of claim 1, wherein the interrogation module comprises at least one of:
the text inquiry module is used for performing inquiry interaction with the target user according to text data corresponding to the standardized questions;
the voice inquiry module is used for performing inquiry interaction with the target user according to the voice data corresponding to the standardized questions;
and the video inquiry module is used for performing inquiry interaction with the target user according to the video data corresponding to the standardized questions.
4. The preliminary screening for depression multimedia-assisted interrogation system of claim 3,
the voice inquiry module is also used for carrying out voice synthesis according to the standardized questions so as to obtain the corresponding voice packet of the virtual doctor;
the video inquiry module is also used for carrying out video synthesis according to the standardized questions so as to obtain corresponding virtual images.
5. The preliminary depression-screening-oriented multimedia-assisted interrogation system of any one of claims 1 to 4, further comprising a questionnaire module for presenting the PHQ9 questionnaire to the target user and obtaining questionnaire information of the target user.
6. The preliminary screening for depression-oriented multimedia-assisted interrogation system of claim 5, further comprising a data storage module for storing the PHQ9 questionnaire, questionnaire information, interrogation content and interrogation data.
7. The preliminary screening for depression multimedia-assisted interrogation system of claim 6, wherein the data processing module comprises:
the prediction unit is used for predicting based on the inquiry data through a preset neural network model so as to obtain prediction data;
and the data operation unit is used for determining a corresponding depression inquiry result according to the prediction data, the questionnaire information and the corresponding weight value.
8. The preliminary depression-screening-oriented multimedia-assisted interrogation system according to any one of claims 1 to 4, further comprising an interrogation-and-answer request module, configured to obtain questions corresponding to the interrogation contents from a database, and send interrogation-and-answer requests to the target users.
9. The preliminary screening for depression-oriented multimedia-assisted interrogation system of any one of claims 1-4, further comprising a science popularization module for pushing depression science popularization information to the target user.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011465603.0A CN112582060A (en) | 2020-12-14 | 2020-12-14 | Multimedia auxiliary inquiry system for depression preliminary screening |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011465603.0A CN112582060A (en) | 2020-12-14 | 2020-12-14 | Multimedia auxiliary inquiry system for depression preliminary screening |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112582060A true CN112582060A (en) | 2021-03-30 |
Family
ID=75131871
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011465603.0A Pending CN112582060A (en) | 2020-12-14 | 2020-12-14 | Multimedia auxiliary inquiry system for depression preliminary screening |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112582060A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115331805A (en) * | 2022-07-04 | 2022-11-11 | 深圳市镜象科技有限公司 | Mental disease diagnosis method based on natural language processing and computer equipment |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| AU2003204909A1 (en) * | 2002-06-28 | 2004-01-15 | Pathfinder Psychological Consultancy Pty Ltd | Computer-aided system and method for self-assessment and personalised mental health consultation |
| US20190043501A1 (en) * | 2017-08-02 | 2019-02-07 | Elements of Genius, Inc. | Patient-centered assistive system for multi-therapy adherence intervention and care management |
| CN109524067A (en) * | 2018-10-16 | 2019-03-26 | 安徽医科大学 | A kind of postpartum depression network interfering system |
| CN110222827A (en) * | 2019-06-11 | 2019-09-10 | 苏州思必驰信息科技有限公司 | The training method of text based depression judgement network model |
| CN111540440A (en) * | 2020-04-23 | 2020-08-14 | 深圳市镜象科技有限公司 | Psychological examination method, device, equipment and medium based on artificial intelligence |
-
2020
- 2020-12-14 CN CN202011465603.0A patent/CN112582060A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| AU2003204909A1 (en) * | 2002-06-28 | 2004-01-15 | Pathfinder Psychological Consultancy Pty Ltd | Computer-aided system and method for self-assessment and personalised mental health consultation |
| US20190043501A1 (en) * | 2017-08-02 | 2019-02-07 | Elements of Genius, Inc. | Patient-centered assistive system for multi-therapy adherence intervention and care management |
| CN109524067A (en) * | 2018-10-16 | 2019-03-26 | 安徽医科大学 | A kind of postpartum depression network interfering system |
| CN110222827A (en) * | 2019-06-11 | 2019-09-10 | 苏州思必驰信息科技有限公司 | The training method of text based depression judgement network model |
| CN111540440A (en) * | 2020-04-23 | 2020-08-14 | 深圳市镜象科技有限公司 | Psychological examination method, device, equipment and medium based on artificial intelligence |
Non-Patent Citations (1)
| Title |
|---|
| 韩佳丽等: "人工智能在抑郁症领域中应用的研究进展", 《北京医学》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115331805A (en) * | 2022-07-04 | 2022-11-11 | 深圳市镜象科技有限公司 | Mental disease diagnosis method based on natural language processing and computer equipment |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109754886A (en) | Therapeutic scheme intelligent generating system, method and readable storage medium storing program for executing, electronic equipment | |
| WO2023178971A1 (en) | Internet registration method, apparatus and device for seeking medical advice, and storage medium | |
| CN111524580A (en) | Virus screening and epidemic prevention system and method based on neural network | |
| CN110619959A (en) | Intelligent triage method and system | |
| WO2022041722A1 (en) | Hospital guidance data acquisition method and apparatus, and computer device and storage medium | |
| CN111145903B (en) | Method and device for acquiring vertigo inquiry text, electronic equipment and inquiry system | |
| JP7115693B2 (en) | Diagnosis support system, diagnosis support device and diagnosis support method | |
| CN109478259A (en) | Medical advice supports tool | |
| CN111564223A (en) | Infectious disease survival probability prediction method, and prediction model training method and device | |
| WO2020253391A1 (en) | Pre-examination information interaction method based on data analysis and related device | |
| CN111008269A (en) | Data processing method and device, storage medium and electronic terminal | |
| CN115719334A (en) | Medical image evaluation method, device, equipment and medium based on artificial intelligence | |
| Boudin et al. | Positional language models for clinical information retrieval | |
| CN112396748A (en) | Physical examination queuing processing method and device, electronic equipment and storage medium | |
| CN112768070A (en) | Mental health evaluation method and system based on dialogue communication | |
| CN118098585A (en) | Medical AI assistant implementation method and system based on data driving and large model | |
| CN112582060A (en) | Multimedia auxiliary inquiry system for depression preliminary screening | |
| CN111161820A (en) | Oral health management system | |
| CN114743647A (en) | Medical data processing method, device, equipment and storage medium | |
| CN111488500B (en) | Medical problem information processing method, device and storage medium | |
| CN110648754A (en) | Department recommendation method, device and equipment | |
| JP2019101654A (en) | Health management assisting device, method, and program | |
| CN116936117A (en) | Chronic disease big data identification and analysis processing method based on AI analysis model | |
| CN112614584A (en) | Method, system and medium for voice and text transcription aided diagnosis of depression | |
| JP2023175142A (en) | Disease evaluation index calculation system, method, and program |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |