CN116580842A - Medical diagnosis data interaction platform combining artificial intelligence - Google Patents
Medical diagnosis data interaction platform combining artificial intelligence Download PDFInfo
- Publication number
- CN116580842A CN116580842A CN202310863432.4A CN202310863432A CN116580842A CN 116580842 A CN116580842 A CN 116580842A CN 202310863432 A CN202310863432 A CN 202310863432A CN 116580842 A CN116580842 A CN 116580842A
- Authority
- CN
- China
- Prior art keywords
- unit
- patient
- disease
- interaction
- doctor
- 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
- 230000003993 interaction Effects 0.000 title claims abstract description 111
- 238000003745 diagnosis Methods 0.000 title claims abstract description 42
- 238000013473 artificial intelligence Methods 0.000 title claims abstract description 21
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 claims abstract description 154
- 201000010099 disease Diseases 0.000 claims abstract description 136
- 208000024891 symptom Diseases 0.000 claims abstract description 34
- 238000004458 analytical method Methods 0.000 claims abstract description 27
- 238000012545 processing Methods 0.000 claims abstract description 27
- 238000012795 verification Methods 0.000 claims abstract description 21
- 230000002265 prevention Effects 0.000 claims abstract description 17
- 238000000034 method Methods 0.000 claims abstract description 10
- 238000004891 communication Methods 0.000 claims description 11
- 230000006806 disease prevention Effects 0.000 claims description 11
- 230000002457 bidirectional effect Effects 0.000 claims description 5
- 230000015572 biosynthetic process Effects 0.000 claims description 3
- 230000003750 conditioning effect Effects 0.000 claims description 3
- 235000006694 eating habits Nutrition 0.000 claims description 3
- 238000010129 solution processing Methods 0.000 claims description 3
- 238000007689 inspection Methods 0.000 abstract description 2
- 239000011159 matrix material Substances 0.000 description 7
- 238000004364 calculation method Methods 0.000 description 6
- 230000036541 health Effects 0.000 description 3
- 230000008030 elimination Effects 0.000 description 2
- 238000003379 elimination reaction Methods 0.000 description 2
- 230000004044 response Effects 0.000 description 2
- 208000027418 Wounds and injury Diseases 0.000 description 1
- 230000004913 activation Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 239000008280 blood Substances 0.000 description 1
- 210000004369 blood Anatomy 0.000 description 1
- 230000006378 damage Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 208000014674 injury Diseases 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000035790 physiological processes and functions Effects 0.000 description 1
- 238000004393 prognosis Methods 0.000 description 1
- 238000013138 pruning Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
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
- 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
- G16H10/60—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
-
- 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
- G16H15/00—ICT specially adapted for medical reports, e.g. generation or transmission thereof
-
- 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
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
-
- 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
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
- G16H20/60—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to nutrition control, e.g. diets
-
- 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
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
- G16H20/70—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to mental therapies, e.g. psychological therapy or autogenous training
-
- 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
- G16H80/00—ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Landscapes
- Health & Medical Sciences (AREA)
- Engineering & Computer Science (AREA)
- Medical Informatics (AREA)
- Public Health (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Epidemiology (AREA)
- Biomedical Technology (AREA)
- Pathology (AREA)
- Databases & Information Systems (AREA)
- Data Mining & Analysis (AREA)
- Nutrition Science (AREA)
- Child & Adolescent Psychology (AREA)
- Developmental Disabilities (AREA)
- Hospice & Palliative Care (AREA)
- Psychiatry (AREA)
- Psychology (AREA)
- Social Psychology (AREA)
- Medical Treatment And Welfare Office Work (AREA)
Abstract
The invention discloses a medical diagnosis data interaction platform combining artificial intelligence, which relates to the technical field of medical interaction, and provides the following scheme, wherein the medical diagnosis data interaction platform comprises a patient login unit, a user verification unit, a disease checking unit and a doctor-patient interaction unit, wherein the patient login unit is used for a patient to log in the medical diagnosis data interaction platform; the user authentication unit performs authentication verification of the patient identity on the transmitted data information; the disorder viewing unit performs a viewing of the examination report on the patient. The invention can not only carry out contrast analysis processing on the symptom characteristics on the patient inspection report through the symptom analysis unit, but also provide a good prevention method and a good treatment means, and can also carry out video interaction or man-machine interaction selection on the newly registered patient according to the own symptoms and doctors through the doctor-patient interaction unit, and carry out video interaction or man-machine interaction selection processing on the patient after the patient has been treated in the hospital, thereby effectively improving the efficiency and convenience of medical diagnosis interaction.
Description
Technical Field
The invention relates to the technical field of medical interaction, in particular to a medical diagnosis data interaction platform combining artificial intelligence.
Background
The medical diagnosis is to judge the spirit and physical state of people from the medical angle, judge the health state, labor capacity and a certain specific physiological process of normal people, judge blood relationship and injury property by judicial departments, and is the most extensive diagnosis for understanding diseases, which is the premise of treatment, prognosis and prevention, but the prior medical diagnosis requires that patients carry diagnosis reports on the surface to communicate with doctors for consultation treatment, the life arrangement of people is relatively tension, and a few minor diseases often lead to serious minor problems due to no free time to communicate with hospitals after diagnosis, and meanwhile, a plurality of patients are prevented from communicating with doctors due to private symptoms, so that a medical diagnosis data interaction platform combining artificial intelligence is provided.
Disclosure of Invention
The invention provides a medical diagnosis data interaction platform combining artificial intelligence to solve the defects in the prior art.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
the medical diagnosis data interaction platform combining the artificial intelligence comprises a patient login unit, a user verification unit, a disease checking unit and a doctor-patient interaction unit, wherein the patient login unit is used for carrying out medical diagnosis data interaction platform login processing on a patient through a patient name, a doctor-card number or a doctor-insurance card number, and sending logged data information to the user verification unit;
the user authentication unit is used for performing authentication verification of the identity of the patient on the data information sent by the patient login unit, inquiring whether the logged patient has a diagnosis record in the home or not, entering the disease checking unit after checking that the patient has a medical record in the home, and entering the doctor-patient interaction unit if a new patient without the medical record exists;
the disease checking unit is used for checking and processing the check report of the patient with the visit record in the hospital, and the patient can enter the doctor-patient interaction unit if the check report is in doubt or the doctor needs to communicate and inquire after checking;
the doctor-patient interaction unit is used for selecting and processing video interaction or man-machine interaction which is not clear for the disease of the newly registered patient and which is required to communicate with the doctor when the patient has a questionable report of the examination result after the patient has been in the hospital.
The medical diagnosis system further comprises a doctor login unit, a medical record uploading unit, a disease data acquisition unit, a disease analysis unit, a database and a disease answering unit, wherein the doctor login unit is used for carrying out login processing of a medical diagnosis data interaction platform according to the name and the department number of a doctor in the hospital;
the medical record uploading unit is used for finishing diagnosis report data information of the patient after the doctor enters the medical diagnosis data interaction platform, completing filling of medical records, carrying out system uploading processing, and simultaneously sending the uploaded medical record data information to the disease data acquisition unit;
the medical record uploading unit is used for uploading medical record data information to the medical record data acquisition unit, and sending the medical record data information to the medical record analysis unit;
the disease analyzing unit is used for retrieving disease data information stored in the database according to the symptom characteristics sent by the disease data acquisition unit, comparing and analyzing the disease data information searched in the database with the symptom characteristics on the patient examination report, providing a good prevention method and a good treatment means, and sending the analyzed disease data information to the disease checking unit;
the database is used for uniformly storing common symptom data information and relevant symptom data information of some difficult and complicated symptoms, so that inquiry, calling and processing are facilitated;
the symptom solving unit is used for carrying out detailed text description solving processing on some symptom problems which are presented after the patient carries out doctor-patient interaction.
Further, the doctor-patient interaction unit comprises a video interaction module and a man-machine interaction module;
the video interaction module is used for carrying out video face-to-face disease problem communication and solution processing on the patient and the corresponding doctor;
the man-machine interaction module is used for AR artificial intelligence communication of patients who are unwilling to carry out face-to-face video communication with doctors, and simultaneously carries out consultation treatment of symptoms and sends the proposed problems to the symptom answering unit.
Further, the disorder analysis unit comprises a disorder introduction module, a disorder prevention module and a disorder management module;
the disease introduction module is used for introducing and describing corresponding diseases by retrieving corresponding disease data information in the database according to the disease data information extracted by the disease data acquisition unit, and sending the disease data information to the disease prevention module;
the disease prevention module is used for analyzing the formation cause of the disease and carrying out prevention suggestion treatment on the life, work and eating habits of individuals in future according to the analysis result;
the disease treatment module is used for a patient to carry out corresponding treatment and conditioning methods according to the prevention suggestions provided by the disease prevention module, and the elimination of the disease is achieved by perfecting the treatment mode of the patient under the disease, so that the health state is achieved.
Further, the output end of the patient login unit is connected with the input end of the user verification unit, the output end of the user verification unit is respectively connected with the input ends of the disease checking unit and the doctor-patient interaction unit, the output end of the disease checking unit is connected with the input end of the doctor-patient interaction unit, the output end of the doctor-patient interaction unit is connected with the input end of the disease answering unit, the output end of the disease answering unit is connected with the input end of the database, and the database is in bidirectional connection with the disease analysis unit;
further, the output end of the doctor login unit is connected with the input ends of the medical record uploading unit, the doctor-patient interaction unit and the disease response unit respectively, the output end of the medical record uploading unit is connected with the input end of the disease data acquisition unit, the output end of the disease data acquisition unit is connected with the input end of the disease analysis unit, and the output end of the disease analysis unit is connected with the input end of the disease viewing unit.
Further, the output end of the disease data acquisition unit is connected with the input end of the disease introduction module, the output end of the disease introduction module is connected with the input end of the disease prevention module, the output end of the disease prevention module is connected with the input end of the disease treatment module, the output end of the disease treatment module is connected with the input end of the disease checking unit, and the disease introduction module is connected with the database in a bidirectional manner.
Further, the output end of the user verification unit is respectively connected with the input ends of the video interaction module and the man-machine interaction module, the output end of the disease checking unit is respectively connected with the input ends of the video interaction module and the man-machine interaction module, and the output end of the doctor login unit is connected with the input end of the video interaction module.
Compared with the prior art, the invention has the beneficial effects that:
the invention can not only carry out contrast analysis processing on the symptom characteristics on the patient inspection report through the symptom analysis unit, but also provide a good prevention method and a good treatment means, and can also carry out video interaction or man-machine interaction selection on the newly registered patient according to the own symptoms and doctors through the doctor-patient interaction unit, and carry out video interaction or man-machine interaction selection processing on the patient after the patient has been treated in the hospital, thereby effectively improving the efficiency and convenience of medical diagnosis interaction.
Drawings
FIG. 1 is a block diagram of an overall system of an artificial intelligence-based medical diagnostic data interaction platform according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings are merely for convenience in describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the present invention.
Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more of the described features. In the description of the present invention, the meaning of "a plurality" is two or more, unless explicitly defined otherwise. Furthermore, the terms "mounted," "connected," "coupled," and "connected" are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the terms in the present invention will be understood by those skilled in the art in detail, and the present invention will be further described in detail with reference to the accompanying drawings.
Examples: referring to fig. 1: the medical diagnosis data interaction platform combining the artificial intelligence comprises a patient login unit, a user verification unit, a disease checking unit and a doctor-patient interaction unit, wherein the patient login unit is used for carrying out medical diagnosis data interaction platform login processing on a patient through a patient name, a doctor-examination card number or a doctor-insurance card number, and sending logged data information to the user verification unit;
the user authentication unit is used for performing authentication verification of the identity of the patient on the data information sent by the patient login unit, inquiring whether the logged patient has a diagnosis record in the home or not, entering the disease checking unit after checking that the patient has a medical record in the home, and entering the doctor-patient interaction unit if a new patient without the medical record exists;
the disease checking unit is used for checking and processing the check report of the patient with the visit record in the hospital, and the patient can enter the doctor-patient interaction unit if the check report is in question or the doctor needs to be communicated and inquired after checking;
the doctor-patient interaction unit is used for selecting and processing video interaction or man-machine interaction which is used for newly registering the disease of the patient and has the questionable need of communicating with the doctor for the examination result report of the patient after the patient is treated in the hospital.
The invention also comprises a doctor login unit, a medical record uploading unit, a disease data acquisition unit, a disease analysis unit, a database and a disease answering unit;
the doctor login unit is used for carrying out login processing of the medical diagnosis data interaction platform according to the name and the department number of the doctor in the hospital;
the medical record uploading unit is used for finishing diagnosis report data information of the patient after the doctor enters the medical diagnosis data interaction platform, completing filling of medical records, carrying out system uploading processing, and simultaneously sending the uploaded medical record data information to the disease data acquisition unit;
the medical record uploading unit is used for uploading medical record data information to the medical record data acquisition unit, and sending the medical record data information to the medical record analyzing unit;
the disease analyzing unit is used for retrieving disease data information stored in the database according to the symptom characteristics sent by the disease data collecting unit, comparing and analyzing the disease data information searched in the database with the symptom characteristics on the patient examination report, providing a good prevention method and a good treatment means, sending the analyzed disease data information to the disease checking unit, and carrying out learning calculation according to the medical characteristics by the disease analyzing unit, wherein the medical characteristic learning calculation formula is as follows:
；
；
；
wherein->For the (e+1) th medical service skip learning feature of the (u) th medical service element, sigma is the activation function, ws is the skip weight of the (u) th medical service element at the (e+1) th layer,/for the (u) th medical service element>For the e-th healthcare jump learning feature of the u-th healthcare element,/->For entry associated with the u-th healthcare elementSum of the e-th entry jump learning features of the element->For the e-th entry jump learning feature of the entry element associated with the u-th medical service element,/for the entry element associated with the u-th medical service element>The sum of the e-th healthcare skip learning features for the healthcare element associated with the u-th healthcare element +.>B) learning features for an e-th healthcare jump of a healthcare element associated with the u-th healthcare element s The jump service feature of the (e+1) th layer for the (u) th medical service element;
wherein the method comprises the steps ofIs the (e+1) th entry jump learning feature of the (i) th entry element, ws is the jump weight of the (i) th entry element at the (e+1) th layer,/a +.>The e-th entry jump learning feature for the i-th entry element,/-th entry element>The sum of the e-th healthcare skip learning features for the healthcare element associated with the i-th entry element +.>B) learning features for an e-th healthcare jump of a healthcare element associated with an i-th entry element s The jump service feature of the ith entry element in the (e+1) th layer;
wherein,,0 th healthcare skip learn feature, p, for the u-th healthcare element u For the initial learning feature of the u-th medical service element,/->Learning feature, q, of the 0 th entry jump of the i-th entry element i Initial learning features for the ith term element;
the database is used for uniformly storing common symptom data information and relevant symptom data information of some difficult and complicated symptoms, so that inquiry, calling and processing are facilitated;
the disease solving unit is used for carrying out detailed text description solving processing on a plurality of disease questions which are presented after the patient carries out doctor-patient interaction.
According to the invention, the doctor-patient interaction unit comprises a video interaction module and a man-machine interaction module, wherein the video interaction module is used for carrying out video face-to-face disease problem communication and solution processing on patients and corresponding doctor, and the problem that the patients do not have time to go to a hospital for face-to-face diagnosis consultation with the doctor due to working or life arrangement is effectively relieved through the video interaction module;
the human-computer interaction module is used for carrying out AR artificial intelligence communication on patients who are unwilling to carry out face-to-face video communication with doctors, carrying out consultation treatment of symptoms at the same time, sending the proposed problems to the symptom answering unit, and effectively relieving the embarrassment that the patients are unwilling to carry out diagnosis consultation face-to-face with the doctors through AR artificial intelligence communication in the human-computer interaction module.
In the invention, the disease analyzing unit comprises a disease introduction module, a disease preventing module and a disease treating module, wherein the disease introduction module is used for introducing and describing corresponding diseases by retrieving corresponding disease data information in a database according to the disease data information extracted by the disease data acquisition unit, and simultaneously sending the disease data information to the disease preventing module, and now, the existing case database set L= { L is assumed 1 ，L 2 ，…，L n ，…，L N Each case record in the collection is composed of a plurality of attributes and disease results, i.e. a case record L n From vector < f 1 ，f 2 ，…，f m ，…，f M ，r>A constitution in which f 1 ，f 2 ，…，f m ，…，f M M attribute characteristics of the cases, r is the disease result, and the existing cases to be diagnosed are collected: q= { Q 1 ，q 2 ，…，q k ，…，q K For any one q, there is a similarity vector < d 1 (q，l)，d 2 (q，l)，…，d m (q，l)，…，d M (Q, L) >, where Q ε Q, L ε L, d m (q, l) represents the distance between the case q to be diagnosed and the case record l on the mth attribute feature, based on d m (Q, L) formulas, all d between sets Q and L can be calculated m Distance, in order to facilitate compatibility analysis and calculation;
repeating this procedure for each case, an M covariance matrix A can be obtained, the covariance A of the ith row and jth column of which ij The following formula is shown:
wherein->Is the mean value, A ij Representing whether the two samples deviate from the mean value at the same time, and positive correlation, negative correlation and uncorrelation exist;
the covariance matrix a is then as follows:
calculating covariance matrix A, further analyzing by compatibility analysis method, wherein the compatibility analysis is to analyze the correlation among data attribute members, construct attribute correlation matrix, and analyze the existing M attribute characteristics f 1 ，f 2 ，…，f m ，…，f M Constructing an attribute correlation matrix using a formula:wherein R is ij Representing the i-th attribute f i And the j-th attribute f j The larger the value of the correlation is, the larger the correlation is, and the attribute correlation matrix is obtained by calculation as follows:
the attribute correlation matrix is utilized to extract the attribute with larger correlation from a plurality of attribute characteristics to perform subsequent calculation processing, and pruning processing is performed on the attribute with smaller correlation, so that the compatibility analysis can effectively reduce the redundant attribute of the disease, and the effect of reducing the dimension and the calculation is achieved;
analyzing the formation cause of the symptoms through a symptom prevention module, and carrying out prevention suggestion treatment on the life, work and eating habits of individuals in future according to the analysis result;
the disease treatment module is used for a patient to carry out corresponding treatment and conditioning methods according to the prevention suggestions provided by the disease prevention module, and the elimination of the disease is achieved by perfecting the treatment mode of the patient under the disease, so that the health state is achieved.
In the invention, the output end of the patient login unit is connected with the input end of the user verification unit, the output end of the user verification unit is respectively connected with the input ends of the disease checking unit and the doctor-patient interaction unit, the output end of the disease checking unit is connected with the input end of the doctor-patient interaction unit, the output end of the doctor-patient interaction unit is connected with the input end of the disease answering unit, the output end of the disease answering unit is connected with the input end of the database, and the database is in bidirectional connection with the disease analysis unit;
in the invention, the output end of the doctor login unit is respectively connected with the input ends of the medical record uploading unit, the doctor-patient interaction unit and the disease response unit, the output end of the medical record uploading unit is connected with the input end of the disease data acquisition unit, the output end of the disease data acquisition unit is connected with the input end of the disease analysis unit, and the output end of the disease analysis unit is connected with the input end of the disease checking unit.
In the invention, the output end of the disease data acquisition unit is connected with the input end of the disease introduction module, the output end of the disease introduction module is connected with the input end of the disease prevention module, the output end of the disease prevention module is connected with the input end of the disease treatment module, the output end of the disease treatment module is connected with the input end of the disease checking unit, and the two-way connection between the disease introduction module and the database is realized.
In the invention, the output end of the user verification unit is respectively connected with the input ends of the video interaction module and the man-machine interaction module, the output end of the disease checking unit is respectively connected with the input ends of the video interaction module and the man-machine interaction module, and the output end of the doctor login unit is connected with the input end of the video interaction module.
The foregoing is only a preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art, who is within the scope of the present invention, should make equivalent substitutions or modifications according to the technical scheme of the present invention and the inventive concept thereof, and should be covered by the scope of the present invention.
Claims (8)
1. The medical diagnosis data interaction platform combining artificial intelligence comprises a patient login unit, a user verification unit, a disease checking unit and a doctor-patient interaction unit, and is characterized in that the medical diagnosis data interaction platform comprises a patient login unit, a user verification unit, a doctor-patient interaction unit and a doctor-patient interaction unit;
the patient login unit is used for performing medical diagnosis data interaction platform login processing on a patient through a patient name, a doctor card number or a medical insurance card number, and sending logged data information to the user verification unit;
the user authentication unit is used for performing authentication verification of the identity of the patient on the data information sent by the patient login unit, inquiring whether the logged patient has a diagnosis record in the home or not, entering the disease checking unit after checking that the patient has a medical record in the home, and entering the doctor-patient interaction unit if a new patient without the medical record exists;
the disease checking unit is used for checking and processing the check report of the patient with the visit record in the hospital, and the patient can enter the doctor-patient interaction unit if the check report is in doubt or the doctor needs to communicate and inquire after checking;
the doctor-patient interaction unit is used for selecting and processing video interaction or man-machine interaction which is not clear for the disease of the newly registered patient and which is required to communicate with the doctor when the patient has a questionable report of the examination result after the patient has been in the hospital.
2. The medical diagnosis data interaction platform combining artificial intelligence according to claim 1, further comprising a doctor logging unit, a medical record uploading unit, a disease data acquisition unit, a disease analysis unit, a database and a disease solving unit;
the doctor login unit is used for carrying out login processing of the medical diagnosis data interaction platform according to the name and the department number of the doctor in the hospital;
the medical record uploading unit is used for finishing diagnosis report data information of the patient after the doctor enters the medical diagnosis data interaction platform, completing filling of medical records, carrying out system uploading processing, and simultaneously sending the uploaded medical record data information to the disease data acquisition unit;
the medical record uploading unit is used for uploading medical record data information to the medical record data acquisition unit, and sending the medical record data information to the medical record analysis unit;
the disease analyzing unit is used for retrieving disease data information stored in the database according to the symptom characteristics sent by the disease data acquisition unit, comparing and analyzing the disease data information searched in the database with the symptom characteristics on the patient examination report, providing a good prevention method and a good treatment means, and sending the analyzed disease data information to the disease checking unit;
the database is used for uniformly storing common symptom data information and relevant symptom data information of some difficult and complicated symptoms, so that inquiry, calling and processing are facilitated;
the symptom solving unit is used for carrying out detailed text description solving processing on some symptom problems which are presented after the patient carries out doctor-patient interaction.
3. The medical diagnosis data interaction platform combining artificial intelligence according to claim 2, wherein the doctor-patient interaction unit comprises a video interaction module and a man-machine interaction module;
the video interaction module is used for carrying out video face-to-face disease problem communication and solution processing on the patient and the corresponding doctor;
the man-machine interaction module is used for AR artificial intelligence communication of patients who are unwilling to carry out face-to-face video communication with doctors, and simultaneously carries out consultation treatment of symptoms and sends the proposed problems to the symptom answering unit.
4. The medical diagnostic data interaction platform incorporating artificial intelligence of claim 2, wherein the disorder analysis unit comprises a disorder introduction module, a disorder prevention module, and a disorder management module;
the disease introduction module is used for introducing and describing corresponding diseases by retrieving corresponding disease data information in the database according to the disease data information extracted by the disease data acquisition unit, and sending the disease data information to the disease prevention module;
the disease prevention module is used for analyzing the formation cause of the disease and carrying out prevention suggestion treatment on the life, work and eating habits of individuals in future according to the analysis result;
the disease treatment module is used for a patient to carry out corresponding treatment and conditioning methods according to the prevention suggestions provided by the disease prevention module.
5. The medical diagnosis data interaction platform combining artificial intelligence according to claim 2, wherein the output end of the patient login unit is connected with the input end of the user verification unit, the output end of the user verification unit is connected with the input ends of the disease checking unit and the doctor-patient interaction unit respectively, the output end of the disease checking unit is connected with the input end of the doctor-patient interaction unit, the output end of the doctor-patient interaction unit is connected with the input end of the disease answering unit, the output end of the disease answering unit is connected with the input end of the database, and the database is connected with the disease analysis unit in a bidirectional manner.
6. The medical diagnosis data interaction platform combining artificial intelligence according to claim 2, wherein the output end of the doctor login unit is connected with the input ends of the medical record uploading unit, the doctor-patient interaction unit and the disease answering unit respectively, the output end of the medical record uploading unit is connected with the input end of the disease data acquisition unit, the output end of the disease data acquisition unit is connected with the input end of the disease analysis unit, and the output end of the disease analysis unit is connected with the input end of the disease viewing unit.
7. The medical diagnostic data interaction platform with artificial intelligence according to claim 4, wherein the output end of the disorder data acquisition unit is connected with the input end of the disorder introduction module, the output end of the disorder introduction module is connected with the input end of the disorder prevention module, the output end of the disorder prevention module is connected with the input end of the disorder management module, the output end of the disorder management module is connected with the input end of the disorder viewing unit, and the disorder introduction module is connected with the database in a bidirectional manner.
8. A medical diagnosis data interaction platform in combination with artificial intelligence according to claim 3, wherein the output end of the user verification unit is connected with the input ends of the video interaction module and the man-machine interaction module respectively, the output end of the disease checking unit is connected with the input ends of the video interaction module and the man-machine interaction module respectively, and the output end of the doctor login unit is connected with the input end of the video interaction module.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310863432.4A CN116580842A (en) | 2023-07-14 | 2023-07-14 | Medical diagnosis data interaction platform combining artificial intelligence |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310863432.4A CN116580842A (en) | 2023-07-14 | 2023-07-14 | Medical diagnosis data interaction platform combining artificial intelligence |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116580842A true CN116580842A (en) | 2023-08-11 |
Family
ID=87534652
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310863432.4A Pending CN116580842A (en) | 2023-07-14 | 2023-07-14 | Medical diagnosis data interaction platform combining artificial intelligence |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116580842A (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106021910A (en) * | 2016-05-17 | 2016-10-12 | 重庆医科大学附属永川医院 | Intelligent medical service-based remote disease diagnosis system |
| CN106339581A (en) * | 2016-08-22 | 2017-01-18 | 杨琪珺 | Dual-purpose medical treatment system for doctors and patients |
| CN106934244A (en) * | 2017-03-20 | 2017-07-07 | 龚昕 | A kind of medical treatment and nursing cloud platform based on intelligent terminal |
| CN112927810A (en) * | 2021-03-23 | 2021-06-08 | 崔剑虹 | Smart medical response method based on big data and smart medical cloud computing system |
| CN113707318A (en) * | 2021-08-27 | 2021-11-26 | 深圳百岁欢智能科技有限公司 | Health data analysis method and analysis system based on accurate AI technology |
-
2023
- 2023-07-14 CN CN202310863432.4A patent/CN116580842A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106021910A (en) * | 2016-05-17 | 2016-10-12 | 重庆医科大学附属永川医院 | Intelligent medical service-based remote disease diagnosis system |
| CN106339581A (en) * | 2016-08-22 | 2017-01-18 | 杨琪珺 | Dual-purpose medical treatment system for doctors and patients |
| CN106934244A (en) * | 2017-03-20 | 2017-07-07 | 龚昕 | A kind of medical treatment and nursing cloud platform based on intelligent terminal |
| CN112927810A (en) * | 2021-03-23 | 2021-06-08 | 崔剑虹 | Smart medical response method based on big data and smart medical cloud computing system |
| CN113707318A (en) * | 2021-08-27 | 2021-11-26 | 深圳百岁欢智能科技有限公司 | Health data analysis method and analysis system based on accurate AI technology |
Non-Patent Citations (1)
| Title |
|---|
| 肖鹏等: "基于相容性分析的医疗诊断专家***", 《计算机工程与应用》, pages 3 * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Scott et al. | Is general practitioner decision making associated with patient socio-economic status? | |
| DE69731884T2 (en) | COMPUTER-ASSISTED MEDICAL DIAGNOSTIC AND CONSULTING SYSTEM WITH ACCESS TO A COMMUNICATION NETWORK | |
| US20180315488A1 (en) | Emergency Room Medical Triage, Diagnosis, and Treatment | |
| US20030233250A1 (en) | Systems and methods for managing biological data and providing data interpretation tools | |
| CN105162880A (en) | ACS (Acute Coronary Syndrome) regional synergistic treatment network system and assistant decision-making method thereof | |
| CN114639479A (en) | Intelligent diagnosis auxiliary system based on medical knowledge map | |
| CN111403015A (en) | Internet medical consultation and online diagnosis system and method | |
| CN114334123A (en) | Cognition assessment system suitable for mild cognitive impairment rapid detection | |
| CN112331334A (en) | Big data accurate medical system and method based on intelligent terminal | |
| CN117476217B (en) | Chronic heart disease state of illness trend prediction system | |
| CN115714022A (en) | Neonatal jaundice health management system based on artificial intelligence | |
| CN116434899A (en) | Health record information platform establishment method based on multi-source data | |
| US20020123670A1 (en) | Chronic pain patient diagnostic system | |
| CN107066816B (en) | Medical treatment guidance method and device based on clinical data and server | |
| CN113517044A (en) | Clinical data processing method and system for evaluating citicoline based on pharmacokinetics | |
| Auslander et al. | Comparing social work's role in renal dialysis in Israel and the United States: The practice-based research potential of available clinical information | |
| CN117438070A (en) | Medical inquiry diagnosis system based on intelligent voice interaction | |
| CN116580842A (en) | Medical diagnosis data interaction platform combining artificial intelligence | |
| JP2000099605A (en) | Health examination information analysis server and network health information system | |
| CN115831298A (en) | Clinical trial patient recruitment method and device based on hospital management information system | |
| CN115331837A (en) | Man-machine interaction intelligent inquiry system | |
| US20020128867A1 (en) | Chronic pain patient identification system | |
| Gilligan et al. | Psychopathic and neuropathic pathways to homicide: Examination of Harris and Rice's two-path model of criminal violence in homicide | |
| Wiebe et al. | Describing agreement in the main condition coding field using Canadian ICD-11 inpatient data | |
| CN111460952B (en) | Method, system and prediction system for generating face recognition rule of schizophrenia |
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 | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20230811 |
|
| RJ01 | Rejection of invention patent application after publication |