CN117133448A - Gynecological disease consultation system based on big data - Google Patents
Gynecological disease consultation system based on big data Download PDFInfo
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Abstract
The invention discloses a gynecological disease consultation system based on big data, which relates to the field of disease consultation and comprises a gynecological disease consultation platform, wherein an information registration module, a database module, a propaganda display module, an information inquiry module, a doctor-patient selection module and a medical diagnosis module are arranged in the gynecological disease consultation platform; the information registration module is used for registering the identity of the user using the platform; the database module is used for storing the data information and medical information of the user in the platform; the propaganda display module is used for displaying gynecological disease knowledge; the information inquiry module is used for acquiring the basic condition of the patient and generating medical guidance information; the doctor-patient selection module is used for selecting a corresponding doctor to generate a query application for detailed query according to the doctor guiding information; the medical diagnosis module is used for setting a joint diagnosis group, and doctors in the joint diagnosis group generate diagnosis books to finish the disease consultation of corresponding patients; the invention has the beneficial effect of reducing the misdiagnosis rate of doctors in the platform to a certain extent.
Description
Technical Field
The invention relates to the field of disease inquiry, in particular to a gynecological disease consultation system based on big data.
Background
Along with the development of society and the improvement of living standard of people, the living mode is gradually changed, especially along with the development of the Internet, people can realize the operation of going out through the Internet at home, great convenience is brought to the life of people, along with the popularization of mobile phones, the medical industry is also free from the development of mobile phones, and patients can inquire about related medical problems in the Internet through the mobile phones;
however, many patients cannot recognize the authenticity of the related medical information, the fish is mixed in the network environment, the misdiagnosis rate of the disease consultation platform is gradually increased, and the optimal treatment time is missed by many patients due to the misinformation of the diagnosis results of the online disease consultation; therefore, how to improve the knowledge of patients on common gynecological diseases and how to improve the accuracy of patient consultation diagnosis are problems which need to be solved, and therefore, a gynecological disease consultation system based on big data is provided.
Disclosure of Invention
In order to solve the technical problems, the invention aims to provide a gynecological disease consultation system based on big data.
The aim of the invention can be achieved by the following technical scheme: the gynecological disease consultation system based on big data comprises a gynecological disease consultation platform, wherein an information registration module, a database module, a propaganda display module, an information inquiry module, a doctor-patient selection module and a medical diagnosis module are arranged in the gynecological disease consultation platform;
the information registration module carries out registration verification on the identity information of the patient and the doctor using the gynecological disease consultation platform, and grants login permission to the verified user;
the database module is used for storing related medical information and data information generated in the platform;
the propaganda display module is used for setting and displaying the integrated poster;
the information inquiry module inquires basic conditions of the patient through an artificial intelligence technology, and generates medical guidance information for the patient according to inquiry results;
the doctor-patient selection module is used for enabling a user to select a corresponding doctor to perform detailed query according to the corresponding doctor guiding information, generating a query application, and enabling the doctor to select whether to diagnose the patient according to the query application;
the medical diagnosis module is used for generating a corresponding joint diagnosis group according to the selection result of the doctor inquiry application, integrating the diagnosis results of the corresponding doctors in the joint diagnosis group, generating a corresponding diagnosis book according to the integrated results, and completing the disease consultation of the corresponding patients.
Further, the information registration module is provided with a patient registration unit and a doctor registration unit;
the patient registration unit is used for acquiring the identity information of the patient, checking the identity information of the patient, and granting a corresponding account number and a corresponding password to the checked patient;
the doctor registration unit is used for acquiring doctor identity information, wherein the doctor identity information comprises a doctor practice certificate, a medical science position certificate and a practitioner certificate of a corresponding doctor; and auditing the identity information of the doctor by the gynecological disease consultation platform, if the auditing is passed, granting the corresponding account number and the corresponding password in the gynecological disease consultation platform, and if the auditing is not passed, not granting the corresponding authority.
Further, the database module is provided with a user storage unit and a data storage unit;
the user storage unit is used for storing data generated in corresponding account numbers of the patient and doctor using the gynecological disease consultation platform, and generating corresponding patient storage space and doctor storage space according to the account numbers of the corresponding patient and doctor, wherein the patient storage space stores basic patient information and diagnosis results generated by the corresponding patient on the gynecological disease consultation platform; the doctor storage space stores a diagnosis record generated by a corresponding doctor on the gynecological disease consultation platform, wherein the diagnosis record comprises a corresponding diagnosis book and a diagnosis result feedback satisfaction degree;
the data storage unit is used for storing medical information and consultation information generated in the gynecological disease consultation platform, wherein the medical information comprises pathogenic causes of various gynecological diseases, harm to human bodies, preventive measures and corresponding cases, and the consultation information comprises patient basic information obtained by the information consultation module.
Further, the process of setting and displaying the integrated poster by the propaganda display module comprises the following steps:
the propaganda display module acquires the gynecological disease types with the diagnosis frequency of the first ten in the gynecological disease consultation system through a big data analysis technology, and acquires the pathogenic reasons, harm to human bodies and preventive measures corresponding to the gynecological disease types stored in the database module; integrating the acquired medical information to generate an integrated poster; expert consultation groups are arranged in the propaganda display module; setting not lower than two doctors engaged in gynecological disease diagnosis in the expert consultation group, and sending the generated integrated poster to an account number of a corresponding doctor in the expert consultation group for examination; and if the inspection passes, the integrated poster corresponding to the gynecological diseases with the diagnosis frequency of the first ten is circularly displayed, and if the inspection does not pass, the integrated poster is modified until the inspection passes, and the integrated poster is displayed.
Further, the process of the information inquiry module for inquiring the basic condition of the patient through the artificial intelligence technology comprises the following steps:
the information inquiry module is provided with an intelligent inquiry unit, and the intelligent inquiry unit is provided with an intelligent inquiry window, an inquiry question bank and a corresponding machine learning algorithm; the intelligent inquiry window is used for inquiring related basic conditions of the patient; the query question library is provided with related questions and reference keyword information; acquiring related questions in a query question library, and submitting query answers of the related questions through an intelligent query window by a user; the machine learning algorithm extracts corresponding query keyword information through a query answer of a big data acquisition user, matches the obtained query keyword information with each reference keyword information in a query question library, acquires corresponding matching values, and sorts the obtained matching values; the machine learning algorithm sets a corresponding query link according to the corresponding reference key words, wherein the query link comprises corresponding related questions in a query question library; and obtaining the reference keyword information with the highest matching value, inquiring the patient according to the related questions corresponding to the reference keyword information in the inquiry link, and sequentially repeating the inquiry process until the inquiry is completed, so as to generate the corresponding basic information of the patient.
Further, the process of generating the medical guidance information for the patient by the information inquiry module according to the inquiry result comprises the following steps:
the intelligent analysis unit analyzes and trains the basic information of the patient and the diagnosis result stored in the database module through a deep learning algorithm to construct a disease analysis model, the basic information of the corresponding patient is input into the disease analysis model, and three gynecological disease types with the highest similarity with the basic information of the corresponding patient are generated through the disease analysis model; and generating corresponding doctor guiding information according to the three gynecological disease types, and sending the generated doctor guiding information to a doctor-patient selection module by the intelligent analysis unit.
Further, a data analysis unit and a user operation unit are arranged in the doctor-patient selection module;
the data analysis unit is used for analyzing the diagnosis records of related doctors in the gynecological disease consultation platform, acquiring the diagnosis records corresponding to each doctor account, analyzing the diagnosis records corresponding to each doctor, and sequencing the feedback satisfaction degree of the diagnosis results of the corresponding gynecological disease types in each diagnosis record to acquire the doctor ranking of each gynecological disease type in the gynecological disease consultation platform;
the user operation unit is used for two-way selection of a patient and a doctor, the gynecological disease consultation platform acquires doctor guiding information generated by the corresponding patient, acquires doctor ranking of the corresponding gynecological disease type in the gynecological disease consultation platform according to the corresponding gynecological disease type in the doctor guiding information, sends the doctor ranking to a patient account, the user selects the corresponding doctor by himself to generate a query application, sends the query application to the corresponding doctor account, the doctor of the corresponding gynecological disease type receives the corresponding query application, the corresponding doctor selects whether to agree to the query application, and sends the corresponding basic information of the patient to the account of the corresponding doctor if the corresponding query application is agreed; setting a response time threshold, if the doctor does not select agreement within the response time threshold, rejecting by default, and if the doctor rejects the corresponding inquiry application within the response time threshold, reselecting the corresponding doctor by the patient to send the inquiry application until the doctor agrees to the corresponding inquiry application corresponding to the gynecological disease type.
Further, the medical diagnosis module is provided with a joint diagnosis unit and a user receiving unit;
the combined diagnosis unit is used for acquiring the result selected by the doctor-patient selection module, associating the patient with doctors who agree to inquire about the corresponding gynecological disease types in the application, acquiring account numbers corresponding to the doctors and the patient, and generating a combined diagnosis group, wherein an inquiry window corresponding to the gynecological disease types for inquiring the information of the relevant patient is arranged in the combined diagnosis group, and the questions of the information inquiry of the patients by the doctors of the gynecological disease types in the inquiry window are shared with the answers of the patients; after the inquiry is completed, the doctors in the joint diagnosis group respectively submit diagnostic results, the joint diagnosis unit analyzes the diagnostic results submitted by the doctors and judges whether the diagnostic results submitted by the doctors are consistent, and if so, a diagnostic result generating diagnostic book is sent to the user receiving unit; if the diagnosis results are inconsistent, generating diagnosis abnormal information and sending the diagnosis abnormal information to the account of the corresponding doctor, and submitting the diagnosis results again by the corresponding doctor until the diagnosis results are consistent, generating a diagnosis book and sending the diagnosis book to the user receiving unit;
the user receiving unit is used for receiving the diagnosis books sent by the corresponding joint diagnosis groups by the patient, acquiring the illness states of the patient according to the corresponding diagnosis books, and submitting corresponding diagnosis results to each doctor to feed back satisfaction.
Compared with the prior art, the invention has the beneficial effects that: the propaganda display module is used for carrying out scientific popularization of common gynecological disease knowledge on patients entering the gynecological disease consultation platform, so that the knowledge of the patients on common gynecological diseases is improved to a certain extent; the basic condition of the patient is known through big data and artificial intelligence technology, and the general direction of the gynecological diseases is judged according to the basic information of the patient, so that the diagnosis efficiency of doctors is improved; by setting the joint diagnosis group, three doctors diagnose the patient at the same time, so that the error rate of the doctor in diagnosing the gynecological diseases of the patient is reduced to a certain extent.
Drawings
FIG. 1 is a schematic diagram of the present invention;
Detailed Description
As shown in FIG. 1, the gynecological disease consultation system based on big data comprises a gynecological disease consultation platform, wherein an information registration module, a database module, a propaganda display module, an information query module, a doctor-patient selection module and a medical diagnosis module are arranged in the gynecological disease consultation platform.
The information registration module is used for carrying out authentication registration on a user using the gynecological disease consultation platform, and the specific implementation process comprises the following steps:
the information registration module is provided with a patient registration unit and a doctor registration unit;
the patient registration unit is used for registering the identity information of a patient, and the patient submits the related patient identity information, wherein the patient identity information comprises the name, the mobile phone number, the gender and the age of the patient; the patient registration unit sends the platform verification code to a mobile phone number contained in the patient identity information, and the relevant user uploads the corresponding platform verification code, if the platform verification code is consistent with the sent platform verification code, the corresponding account number and the corresponding password are granted through identity verification; if the identity is inconsistent with the sending, the identity verification is not passed;
the doctor registration unit is used for registering identity information of a doctor, and the doctor submits relevant doctor identity information, wherein the doctor identity information comprises a name, an identity card number, gender, age, a mobile phone number for real-name authentication, a doctor practice certificate, a practice certificate and a medical science and doctor's position certificate; the doctor registration unit checks the mobile phone number, if the verification is passed, the platform verification code is sent to the real-name authentication mobile phone number contained in the identity information, the doctor uploads the corresponding platform verification code, and if the verification is consistent with the sending, the corresponding account number and the corresponding password are granted through the identity verification; if the identity is inconsistent with the sending, the identity verification is not passed.
The database module is used for storing medical data of related patients and other cases in the gynecological disease consultation platform, and the specific implementation process comprises the following steps:
the database module is provided with a user storage unit and a data storage unit;
the user storage unit is used for storing information of doctors and patients using the gynecological disease consultation platform, and is provided with a user storage unit and a data storage unit;
the user storage unit is used for storing data generated in corresponding account numbers of the patient and doctor using the gynecological disease consultation platform, and generating corresponding patient storage space and doctor storage space according to the account numbers of the corresponding patient and doctor, wherein the patient storage space stores basic patient information and diagnosis results generated by the corresponding patient on the gynecological disease consultation platform; the doctor storage space stores a diagnosis record generated by a corresponding doctor on the gynecological disease consultation platform, wherein the diagnosis record comprises a corresponding diagnosis book and a diagnosis result feedback satisfaction degree;
the data storage unit is used for storing medical information and consultation information generated in the gynecological disease consultation platform, wherein the medical information comprises pathogenic causes of various gynecological diseases, harm to human bodies, preventive measures and corresponding cases, and the consultation information comprises patient basic information obtained by the information consultation module.
The propaganda display module sets up and integrates the poster and carries out the process of showing it includes:
the propaganda display module acquires the gynecological disease types with the diagnosis frequency of the first ten in the gynecological disease consultation system through a big data analysis technology, and acquires the pathogenic reasons, harm to human bodies and preventive measures corresponding to the gynecological disease types stored in the database module; integrating the acquired medical information to generate an integrated poster; expert consultation groups are arranged in the propaganda display module; setting not lower than two doctors engaged in gynecological disease diagnosis in the expert consultation group, and sending the generated integrated poster to an account number of a corresponding doctor in the expert consultation group for examination; if the inspection passes, the integrated poster corresponding to the gynecological disease category with the first ten diagnostic frequencies is circularly displayed, and if the inspection does not pass, the integrated poster is modified until the inspection passes, and the integrated poster is displayed;
it should be further noted that, in the implementation process, the circulation display of the integrated poster by the propaganda display module improves the knowledge of the patient about the gynecological diseases with higher diagnosis frequency to a certain extent.
The information inquiry module is used for inquiring the basic condition of the patient and acquiring the basic disease characteristics of the patient, and the specific implementation process comprises the following steps:
the information inquiry module is provided with an intelligent inquiry unit and an intelligent analysis unit;
the intelligent query unit is provided with an intelligent query window, a query question library and a corresponding machine learning algorithm; the intelligent inquiry window is used for inquiring related basic conditions of the patient; the query question library is provided with related questions and reference keyword information; acquiring related questions in a query question library, and submitting query answers of the related questions through an intelligent query window by a user; the machine learning algorithm extracts corresponding query keyword information through a query answer of a big data acquisition user, matches the obtained query keyword information with each reference keyword information in a query question library, acquires corresponding matching values, and sorts the obtained matching values; the machine learning algorithm sets a corresponding query link according to the corresponding reference key words, wherein the query link comprises corresponding related questions in a query question library; acquiring reference keyword information with highest matching value, inquiring the patient according to the related questions corresponding to the reference keyword information in the inquiry link, and sequentially repeating the inquiry process until the inquiry is completed, so as to generate corresponding basic patient information;
the intelligent analysis unit analyzes and trains the basic information of the patient and the diagnosis result stored in the database module through a deep learning algorithm to construct a disease analysis model, the corresponding basic information of the patient is input into the disease analysis model, and three gynecological disease types with highest similarity with the corresponding basic information of the patient are generated through the disease analysis model; and generating corresponding doctor guiding information according to the three gynecological disease types, and sending the generated doctor guiding information to a doctor-patient selection module by the intelligent analysis unit.
The doctor-patient selection module is used for a user to select a corresponding doctor to perform detailed query according to the corresponding doctor guiding information, and generates a query application, and the doctor selects whether to diagnose the patient according to the query application, and the specific implementation process comprises the following steps:
the doctor-patient selection module is provided with a data analysis unit and a user operation unit;
the data analysis unit is used for analyzing the diagnosis records of related doctors in the gynecological disease consultation platform, acquiring the diagnosis records corresponding to each doctor account, analyzing the diagnosis records corresponding to each doctor, and sequencing the feedback satisfaction degree of the diagnosis results of the corresponding gynecological disease types in each diagnosis record to acquire the doctor ranking of each gynecological disease type in the gynecological disease consultation platform;
the user operation unit is used for two-way selection of a patient and a doctor, the gynecological disease consultation platform acquires doctor guiding information generated by the corresponding patient, acquires doctor ranking of the corresponding gynecological disease type in the gynecological disease consultation platform according to the corresponding gynecological disease type in the doctor guiding information, sends the doctor ranking to a patient account, the user selects the corresponding doctor by himself to generate a query application, sends the query application to the corresponding doctor account, the doctor of the corresponding gynecological disease type receives the corresponding query application, the corresponding doctor selects whether to agree to the query application, and sends the corresponding basic information of the patient to the account of the corresponding doctor if the corresponding query application is agreed; setting a response time threshold, if the doctor does not select agreement within the response time threshold, rejecting by default, and if the doctor rejects the corresponding inquiry application within the response time threshold, reselecting the corresponding doctor by the patient to send the inquiry application until the doctor agrees to the corresponding inquiry application corresponding to the gynecological disease type.
The medical diagnosis module is used for generating a corresponding joint diagnosis group according to the selection result of the doctor inquiry application, integrating the diagnosis results of the corresponding doctors in the joint diagnosis group, generating a corresponding diagnosis book according to the integrated results, and completing the disease consultation of the corresponding patients, and the specific implementation process comprises the following steps:
the medical diagnosis module is provided with a joint diagnosis unit and a user receiving unit;
the combined diagnosis unit is used for acquiring the result selected by the doctor-patient selection module, associating the patient with doctors who agree to inquire about the corresponding gynecological disease types in the application, acquiring account numbers corresponding to the doctors and the patient, and generating a combined diagnosis group, wherein an inquiry window corresponding to the gynecological disease types for inquiring the information of the relevant patient is arranged in the combined diagnosis group, and the questions of the information inquiry of the patients by the doctors of the gynecological disease types in the inquiry window are shared with the answers of the patients; after the inquiry is completed, the doctors in the joint diagnosis group respectively submit diagnostic results, the joint diagnosis unit analyzes the diagnostic results submitted by the doctors and judges whether the diagnostic results submitted by the doctors are consistent, and if so, a diagnostic result generating diagnostic book is sent to the user receiving unit; if the diagnosis results are inconsistent, generating diagnosis abnormal information and sending the diagnosis abnormal information to the account of the corresponding doctor, and submitting the diagnosis results again by the corresponding doctor until the diagnosis results are consistent, generating a diagnosis book and sending the diagnosis book to the user receiving unit;
the user receiving unit is used for receiving the diagnosis books sent by the corresponding joint diagnosis groups by the patient, acquiring the illness states of the patient according to the corresponding diagnosis books, submitting the corresponding diagnosis result feedback satisfaction degree to each doctor, and sending the submitted diagnosis result feedback satisfaction degree and the diagnosis result to the database module for storage.
The above embodiments are only for illustrating the technical method of the present invention and not for limiting the same, and it should be understood by those skilled in the art that the technical method of the present invention may be modified or substituted without departing from the spirit and scope of the technical method of the present invention.
Claims (8)
1. The gynecological disease consultation system based on big data is characterized by comprising a gynecological disease consultation platform, wherein an information registration module, a database module, a propaganda display module, an information inquiry module, a doctor-patient selection module and a medical diagnosis module are arranged in the gynecological disease consultation platform;
the information registration module carries out registration verification on the identity information of the patient and the doctor using the gynecological disease consultation platform, and grants login permission to the verified user;
the database module is used for storing related medical information and data information generated in the platform;
the propaganda display module is used for setting and displaying the integrated poster;
the information inquiry module inquires basic conditions of the patient through an artificial intelligence technology, and generates medical guidance information for the patient according to inquiry results;
the doctor-patient selection module is used for enabling a user to select a corresponding doctor to perform detailed query according to the corresponding doctor guiding information, generating a query application, and enabling the doctor to select whether to diagnose the patient according to the query application;
the medical diagnosis module is used for generating a corresponding joint diagnosis group according to the selection result of the doctor inquiry application, integrating the diagnosis results of the corresponding doctors in the joint diagnosis group, generating a corresponding diagnosis book according to the integrated results, and completing the disease consultation of the corresponding patients.
2. The gynecological disease consultation system based on big data according to claim 1, wherein the information registration module is provided with a patient registration unit and a doctor registration unit;
the patient registration unit is used for acquiring the identity information of the patient, checking the identity information of the patient, and granting a corresponding account number and a corresponding password to the checked patient;
the doctor registration unit is used for acquiring doctor identity information, wherein the doctor identity information comprises a doctor practice certificate, a medical science position certificate and a practitioner certificate of a corresponding doctor; and auditing the identity information of the doctor by the gynecological disease consultation platform, if the auditing is passed, granting the corresponding account number and the corresponding password in the gynecological disease consultation platform, and if the auditing is not passed, not granting the corresponding authority.
3. The gynecological disease consultation system based on big data according to claim 2, wherein the database module is provided with a user storage unit and a data storage unit;
the user storage unit is used for storing data generated in corresponding account numbers of the patient and doctor using the gynecological disease consultation platform, and generating corresponding patient storage space and doctor storage space according to the account numbers of the corresponding patient and doctor, wherein the patient storage space stores basic patient information and diagnosis results generated by the corresponding patient on the gynecological disease consultation platform; the doctor storage space stores a diagnosis record generated by a corresponding doctor on the gynecological disease consultation platform, wherein the diagnosis record comprises a corresponding diagnosis book and a diagnosis result feedback satisfaction degree;
the data storage unit is used for storing medical information and consultation information generated in the gynecological disease consultation platform, wherein the medical information comprises pathogenic causes of various gynecological diseases, harm to human bodies, preventive measures and corresponding cases, and the consultation information comprises patient basic information obtained by the information consultation module.
4. The gynecological disease consultation system based on big data according to claim 3, wherein the process of setting and displaying the integrated poster by the propaganda display module includes:
the propaganda display module acquires the gynecological disease types with the diagnosis frequency of the first ten in the gynecological disease consultation system through a big data analysis technology, and acquires the pathogenic reasons, harm to human bodies and preventive measures corresponding to the gynecological disease types stored in the database module; integrating the acquired medical information to generate an integrated poster; expert consultation groups are arranged in the propaganda display module; setting not lower than two doctors engaged in gynecological disease diagnosis in the expert consultation group, and sending the generated integrated poster to an account number of a corresponding doctor in the expert consultation group for examination; and if the inspection passes, the integrated poster corresponding to the gynecological diseases with the diagnosis frequency of the first ten is circularly displayed, and if the inspection does not pass, the integrated poster is modified until the inspection passes, and the integrated poster is displayed.
5. The gynecological disease consultation system based on big data according to claim 4, wherein the information consultation module performs a process of inquiring the basic condition of the patient through artificial intelligence technology includes:
the information inquiry module is provided with an intelligent inquiry unit, and the intelligent inquiry unit is provided with an intelligent inquiry window, an inquiry question bank and a corresponding machine learning algorithm; the intelligent inquiry window is used for inquiring related basic conditions of the patient; the query question library is provided with related questions and reference keyword information; acquiring related questions in a query question library, and submitting query answers of the related questions through an intelligent query window by a user; the machine learning algorithm extracts corresponding query keyword information through a query answer of a big data acquisition user, matches the obtained query keyword information with each reference keyword information in a query question library, acquires corresponding matching values, and sorts the obtained matching values; the machine learning algorithm sets a corresponding query link according to the corresponding reference key words, wherein the query link comprises corresponding related questions in a query question library; and obtaining the reference keyword information with the highest matching value, inquiring the patient according to the related questions corresponding to the reference keyword information in the inquiry link, and sequentially repeating the inquiry process until the inquiry is completed, so as to generate the corresponding basic information of the patient.
6. The gynecological disease consultation system based on big data according to claim 5, wherein the information inquiry module generates medical guidance information for the patient according to the inquiry result includes:
the intelligent analysis unit analyzes and trains the basic information of the patient and the diagnosis result stored in the database module through a deep learning algorithm to construct a disease analysis model, the basic information of the corresponding patient is input into the disease analysis model, and three gynecological disease types with the highest similarity with the basic information of the corresponding patient are generated through the disease analysis model; and generating corresponding doctor guiding information according to the three gynecological disease types, and sending the generated doctor guiding information to a doctor-patient selection module by the intelligent analysis unit.
7. The gynecological disease consultation system based on big data according to claim 6, wherein the doctor-patient selection module is provided with a data analysis unit and a user operation unit;
the data analysis unit is used for analyzing the diagnosis records of related doctors in the gynecological disease consultation platform, acquiring the diagnosis records corresponding to each doctor account, analyzing the diagnosis records corresponding to each doctor, and sequencing the feedback satisfaction degree of the diagnosis results of the corresponding gynecological disease types in each diagnosis record to acquire the doctor ranking of each gynecological disease type in the gynecological disease consultation platform;
the user operation unit is used for two-way selection of a patient and a doctor, the gynecological disease consultation platform acquires doctor guiding information generated by the corresponding patient, acquires doctor ranking of the corresponding gynecological disease type in the gynecological disease consultation platform according to the corresponding gynecological disease type in the doctor guiding information, sends the doctor ranking to a patient account, the user selects the corresponding doctor by himself to generate a query application, sends the query application to the corresponding doctor account, the doctor of the corresponding gynecological disease type receives the corresponding query application, the corresponding doctor selects whether to agree to the query application, and sends the corresponding basic information of the patient to the account of the corresponding doctor if the corresponding query application is agreed; setting a response time threshold, if the doctor does not select agreement within the response time threshold, rejecting by default, and if the doctor rejects the corresponding inquiry application within the response time threshold, reselecting the corresponding doctor by the patient to send the inquiry application until the doctor agrees to the corresponding inquiry application corresponding to the gynecological disease type.
8. The gynecological disease consultation system based on big data according to claim 7, wherein the medical diagnosis module is provided with a joint diagnosis unit and a user receiving unit;
the combined diagnosis unit is used for acquiring the result selected by the doctor-patient selection module, associating the patient with doctors who agree to inquire about the corresponding gynecological disease types in the application, acquiring account numbers corresponding to the doctors and the patient, and generating a combined diagnosis group, wherein an inquiry window corresponding to the gynecological disease types for inquiring the information of the relevant patient is arranged in the combined diagnosis group, and the questions of the information inquiry of the patients by the doctors of the gynecological disease types in the inquiry window are shared with the answers of the patients; after the inquiry is completed, the doctors in the joint diagnosis group respectively submit diagnostic results, the joint diagnosis unit analyzes the diagnostic results submitted by the doctors and judges whether the diagnostic results submitted by the doctors are consistent, and if so, a diagnostic result generating diagnostic book is sent to the user receiving unit; if the diagnosis results are inconsistent, generating diagnosis abnormal information and sending the diagnosis abnormal information to the account of the corresponding doctor, and submitting the diagnosis results again by the corresponding doctor until the diagnosis results are consistent, generating a diagnosis book and sending the diagnosis book to the user receiving unit;
the user receiving unit is used for receiving the diagnosis books sent by the corresponding joint diagnosis groups by the patient, acquiring the illness states of the patient according to the corresponding diagnosis books, and submitting corresponding diagnosis results to each doctor to feed back satisfaction.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118197650A (en) * | 2024-05-17 | 2024-06-14 | 长春中医药大学 | Intelligent monitoring system for evaluating safety of gynecological minimally invasive surgery |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20050251415A1 (en) * | 2004-05-07 | 2005-11-10 | Pak Hon S | System and method for consultation on dermatological disorders |
| CN102663129A (en) * | 2012-04-25 | 2012-09-12 | 中国科学院计算技术研究所 | Medical field deep question and answer method and medical retrieval system |
| CN105912848A (en) * | 2016-04-08 | 2016-08-31 | 南昌大学 | Palm APP based medical service system |
| CN109559830A (en) * | 2018-09-30 | 2019-04-02 | 西南医科大学附属医院 | Smart Verify consulting system and its implementation based on Medicine standard problem base |
| CN109887555A (en) * | 2017-12-06 | 2019-06-14 | 邱正廸 | Medical resource integration system |
| CN110097959A (en) * | 2019-04-25 | 2019-08-06 | 闻康集团股份有限公司 | A kind of quick interrogation system and method online |
| CN111260520A (en) * | 2020-01-10 | 2020-06-09 | 上海市浦东新区公利医院(第二军医大学附属公利医院) | Diagnosis guide and medical guide system based on intelligent voice multi-round inquiry and self-help registration technology |
| CN111415740A (en) * | 2020-02-12 | 2020-07-14 | 东北大学 | Method and device for processing inquiry information, storage medium and computer equipment |
| CN113539460A (en) * | 2021-07-29 | 2021-10-22 | 深圳万海思数字医疗有限公司 | Intelligent diagnosis guiding method and device for remote medical platform |
| CN115662654A (en) * | 2022-09-16 | 2023-01-31 | 康键信息技术（深圳）有限公司 | Intelligent medicine box based medicine management method, device, equipment and storage medium |
| CN115985476A (en) * | 2022-12-09 | 2023-04-18 | 上海镁信健康科技股份有限公司 | Internet diagnosis and treatment triage order dispatching method based on AI intelligent diagnosis guide technology |
-
2023
- 2023-10-23 CN CN202311371141.XA patent/CN117133448B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20050251415A1 (en) * | 2004-05-07 | 2005-11-10 | Pak Hon S | System and method for consultation on dermatological disorders |
| CN102663129A (en) * | 2012-04-25 | 2012-09-12 | 中国科学院计算技术研究所 | Medical field deep question and answer method and medical retrieval system |
| CN105912848A (en) * | 2016-04-08 | 2016-08-31 | 南昌大学 | Palm APP based medical service system |
| CN109887555A (en) * | 2017-12-06 | 2019-06-14 | 邱正廸 | Medical resource integration system |
| CN109559830A (en) * | 2018-09-30 | 2019-04-02 | 西南医科大学附属医院 | Smart Verify consulting system and its implementation based on Medicine standard problem base |
| CN110097959A (en) * | 2019-04-25 | 2019-08-06 | 闻康集团股份有限公司 | A kind of quick interrogation system and method online |
| CN111260520A (en) * | 2020-01-10 | 2020-06-09 | 上海市浦东新区公利医院(第二军医大学附属公利医院) | Diagnosis guide and medical guide system based on intelligent voice multi-round inquiry and self-help registration technology |
| CN111415740A (en) * | 2020-02-12 | 2020-07-14 | 东北大学 | Method and device for processing inquiry information, storage medium and computer equipment |
| CN113539460A (en) * | 2021-07-29 | 2021-10-22 | 深圳万海思数字医疗有限公司 | Intelligent diagnosis guiding method and device for remote medical platform |
| CN115662654A (en) * | 2022-09-16 | 2023-01-31 | 康键信息技术（深圳）有限公司 | Intelligent medicine box based medicine management method, device, equipment and storage medium |
| CN115985476A (en) * | 2022-12-09 | 2023-04-18 | 上海镁信健康科技股份有限公司 | Internet diagnosis and treatment triage order dispatching method based on AI intelligent diagnosis guide technology |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118197650A (en) * | 2024-05-17 | 2024-06-14 | 长春中医药大学 | Intelligent monitoring system for evaluating safety of gynecological minimally invasive surgery |
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|---|---|
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