CN117316438A - AI-based traditional Chinese medicine expert remote medical auxiliary system - Google Patents
AI-based traditional Chinese medicine expert remote medical auxiliary system Download PDFInfo
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- 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
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- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06311—Scheduling, planning or task assignment for a person or group
- G06Q10/063112—Skill-based matching of a person or a group to a task
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- G—PHYSICS
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- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
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- 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
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- 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
Abstract
The invention relates to the technical field of telemedicine, in particular to an AI-based traditional Chinese medical expert telemedicine auxiliary system, which comprises a user login module, a data storage module, an information transmission module and an analysis module, wherein the user login module is used for verifying login information of a user, the data storage module is used for storing a diagnosis record of a doctor and a diagnosis record of a traditional Chinese medical expert, the information transmission module is used for uploading illness state data of the doctor to a server, the analysis module is used for calculating the diagnosis probability of any expert in the diagnosis record of the doctor to judge whether the expert is matched, if the matching standard is not met, whether the expert in the diagnosis record of the expert is matched or not is judged according to the second time of the diagnosis times of the doctor, which is the same as the doctor, if the matching parameter is not met, the calculated matching parameter of the expert is matched with the expert again, and when the matching parameter is not met with the matching standard, the matching parameter is calculated and adjusted to match the matching parameter. The invention improves the accuracy of doctor-patient matching and improves the diagnosis efficiency of the expert.
Description
Technical Field
The invention relates to the technical field of telemedicine, in particular to an AI-based traditional Chinese medicine expert telemedicine auxiliary system.
Background
Chinese patent publication No.: CN106874677B discloses a remote assisted medical method, device and doctor's advice platform system, comprising: receiving doctor order information uploaded by a doctor, a disease type corresponding to the doctor order information and account information of the doctor through a doctor client of the doctor order platform; the doctor's advice platform is provided with a doctor client and a patient client, and the doctor's advice information comprises one or more of audio, video, pictures and characters; binding the medical advice information, the disease type and the account information of the doctor, and storing the medical advice information, the disease type and the account information of the doctor into a database of a medical advice platform; searching account information of a patient corresponding to a doctor from a corresponding relation between the doctor and the patient stored in advance in a doctor advice platform; and pushing the medical advice information bound with the disease type and the account information of the doctor to a patient client of the patient through a medical advice platform according to the account information of the patient. The invention reduces the workload of doctor seeing doctor and improves the experience of patient seeing doctor.
However, the prior art cannot match the doctor according to the actual condition of the doctor, so that the doctor cannot often obtain the doctor's diagnosis more aiming at the condition, and the doctor-patient matching accuracy is low, thereby reducing the doctor's diagnosis efficiency.
Disclosure of Invention
Therefore, the invention provides an AI-based remote medical assistance system for traditional Chinese medicine specialists, which is used for solving the problem that in the prior art, the specialist's diagnosis efficiency is low because the specialists cannot be matched according to the actual illness state of the doctor.
In order to achieve the above object, the present invention provides an AI-based remote medical assistance system for a chinese medical specialist, comprising:
the user login module is used for verifying login information of a user and connecting the verified user with the server, wherein the user comprises a doctor and a Chinese medical expert;
the data storage module comprises a first storage unit for storing the diagnosis records of the patients and a second storage unit for storing the diagnosis records of the Chinese medical specialists;
the information transmission module is used for uploading the illness state data of the doctor to the server and linking the doctor and the Chinese medical expert for information transmission;
the analysis module is respectively connected with the user login module, the data storage module and the information transmission module and is used for calculating the diagnosis probability of any expert in the diagnosis records of the consultants so as to judge whether the experts are matched, if the matching criteria are not met, whether the experts in the diagnosis records are matched according to the second judgment of the times of the diagnosis of the same illness state of the consultants in the diagnosis records of the experts, if the matching criteria are not met, the calculated matching parameters of the experts are used as the matching experts of the consultants again, and when the matching parameters do not meet the matching criteria, the matching parameters are calculated and adjusted so as to match the experts.
Further, the user login module includes:
the Chinese medicine expert login unit is used for verifying login information of the Chinese medicine expert and connecting the verified Chinese medicine expert with the server;
the doctor registering unit is used for verifying the registering information of the doctor and connecting the doctor passing the verification with the server.
Further, the analysis module calculates the diagnosis probability of any expert in the diagnosis records of the consultant to judge whether to match the expert;
and if the probability of the diagnosis is larger than a second preset probability value, the analysis module judges that the corresponding experts are matched, and the experts with the probability of the diagnosis larger than the second preset probability value are matched according to the descending order of the probability of the diagnosis.
Further, the analysis module compares the diagnosis probability with a first preset probability value under the condition that the calculated diagnosis probability is smaller than or equal to the second preset probability value, and if the diagnosis probability is larger than the first preset probability value, the analysis module extracts the diagnosis times of the same illness state as the doctor in the diagnosis records of the corresponding expert, and judges whether to match the expert or not according to the diagnosis times;
the first preset probability value is smaller than the second preset probability value.
Further, the analysis module corrects the visit probability that is greater than the first preset probability value and less than or equal to the second preset probability value according to the extracted visit times, if the corrected visit probability is greater than the second preset probability value, the analysis module judges that the corresponding experts are matched, and matches the experts with the corrected visit probability that is greater than the second preset probability value according to the descending order of the corrected visit probability.
Further, a plurality of correction coefficients are arranged in the analysis module, the analysis module is provided with a plurality of correction modes aiming at the diagnosis probability based on the extracted diagnosis times, and each correction mode corresponds to a different correction coefficient.
Further, the analysis module determines that no matching is performed on the expert when the calculated probability of the diagnosis is equal to or smaller than the first preset probability value or the corrected probability of the diagnosis is equal to or smaller than the second preset probability value, calculates a matching parameter of any expert according to the following formula, and sets:
；
wherein F is a matching parameter, T is the expert's visit time, N is the expert's total number of visits, N is the number of visits of the same illness state as the patient in the total number of visits, T0 is the preset standard visit time, N0 is the preset standard visit total number, N0 is the number of visits of the same illness state as the patient in the preset standard visit total number, and alpha, beta and gamma are corresponding weight coefficients.
Further, the analysis module matches the expert according to the matching parameters;
and the analysis module compares the matching parameters with preset matching comparison parameters, and if the matching parameters are larger than the matching comparison parameters, the analysis module matches the experts with the matching parameters larger than the matching comparison parameters according to descending order of the matching parameters.
Further, the analysis module determines that the expert is not matched under the condition that the matching parameters are smaller than or equal to the matching comparison parameters, calculates and adjusts the comparison parameters according to the following formula, and sets:
；
wherein Y is an adjustment contrast parameter, C is an expert score, and C0 is a preset standard expert score.
Further, the analysis module adjusts the matching parameters according to the adjustment comparison parameters, and matches the expert according to the adjusted matching parameters;
the analysis module is provided with a plurality of adjusting coefficients, the analysis module is provided with a plurality of adjusting modes aiming at the matching parameters based on the adjusting comparison parameters, each adjusting mode corresponds to different adjusting coefficients, if the adjusted matching parameters are larger than the matching comparison parameters, the analysis module matches the expert according to descending order arrangement sequences of the adjusted matching parameters, and if the adjusted matching parameters are smaller than or equal to the matching comparison parameters, the analysis module matches the expert according to descending order arrangement sequences of the consultation probability of the expert in the consultation records of the consultation person.
Compared with the prior art, the invention has the beneficial effects that the analysis module firstly takes the diagnosis record of the doctor as a reference when the expert is matched with any doctor, and when the diagnosis probability of the expert is larger than the second preset probability value, the expert is informed of the illness state of the doctor, so that the expert is helped to comprehensively know the illness state and the physical condition of the doctor, the communication efficiency is improved, the accuracy of the expert on the illness state treatment of the doctor is also improved, and the diagnosis efficiency of the expert is further improved.
Further, the first preset probability value and the second preset probability value are set to represent the degree of understanding of the expert on the illness state of the patient, so that the expert is matched with the patient better, and a better diagnosis effect is achieved.
Further, the analysis module of the invention indicates that the expert has a certain knowledge on the illness state of the patient when the calculated diagnosis probability is smaller than or equal to the second preset probability value and if the diagnosis probability is larger than the first preset probability value, the diagnosis probability is corrected according to the diagnosis times of the same illness state of the patient in the diagnosis records of the expert, whether the expert is matched is judged for the second time according to the corrected diagnosis probability, and the diagnosis experience of the expert on the same illness state is fully considered, thereby improving the accuracy of the expert on the illness state treatment of the patient and further improving the diagnosis efficiency of the expert.
Further, under the condition that the diagnosis probability of an expert does not accord with the matching condition, the matching parameter of any expert is calculated, the matching parameter is the characteristic parameter of the matching index of the expert relative to the person to be diagnosed, when the expert looks more the total times of diagnosis, the more the times of diagnosis of the same illness state as the person to be diagnosed in the total times of diagnosis are, and the longer the time of diagnosis is, the stronger the professional of the expert in the diagnosis of the illness state is, the higher the matching degree with the person to be diagnosed is, the diagnosis experience of the person to be diagnosed can be improved, and the diagnosis efficiency of the expert is also improved.
Further, under the condition that the matching parameters do not meet the matching conditions, the analysis module calculates the diagnosis probability of the condition of the expert in the total times of scoring and diagnosis of the expert and the doctor for representing the matching degree of the expert and the doctor, adjusts the matching parameters according to the adjustment comparison parameters by calculating the adjustment comparison parameters, and selects the corresponding adjustment coefficients according to the adjustment comparison parameters to determine the matched expert, so that the doctor-patient matching accuracy is further improved, and the diagnosis efficiency of the expert is further improved.
Further, when the adjusted matching parameters are smaller than or equal to the matching comparison parameters, the analysis module indicates that the matching degree of the expert is lower, at this time, the analysis module matches according to the diagnosis probability of the expert in the diagnosis records of the doctor, the expert knows the illness state of the doctor to a certain extent, and the doctor-patient matching accuracy can be improved to the greatest extent.
Drawings
FIG. 1 is a block diagram of an AI-based remote medical assistance system for a TCM expert in accordance with an embodiment of the present invention;
FIG. 2 is a block diagram of a user login module in an AI-based TCM expert telemedicine assistance system according to an embodiment of the present invention;
FIG. 3 is a block diagram illustrating a data storage module in an AI-based remote medical assistance system for a TCM expert according to an embodiment of the present invention;
fig. 4 is a further structural block diagram of an AI-based remote medical assistance system for a chinese medical specialist according to an embodiment of the present invention.
Detailed Description
In order that the objects and advantages of the invention will become more apparent, the invention will be further described with reference to the following examples; it should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are merely for explaining the technical principles of the present invention, and are not intended to limit the scope of the present invention.
It should be noted that, in the description of the present invention, terms such as "upper," "lower," "left," "right," "inner," "outer," and the like indicate directions or positional relationships based on the directions or positional relationships shown in the drawings, which are merely for convenience of description, and do not indicate or imply that the apparatus or elements must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limiting the present invention.
Furthermore, it should be noted that, in the description of the present invention, unless explicitly specified and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be either fixedly connected, detachably connected, or integrally connected, for example; 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 above terms in the present invention can be understood by those skilled in the art according to the specific circumstances.
Referring to fig. 1 to 4, the AI-based medical expert telemedicine assistance system of the present invention includes:
the user login module is used for verifying login information of a user and connecting the verified user with the server, wherein the user comprises a doctor and a Chinese medical expert;
the data storage module comprises a first storage unit for storing the diagnosis records of the patients and a second storage unit for storing the diagnosis records of the Chinese medical specialists;
the information transmission module is used for uploading the illness state data of the doctor to the server and linking the doctor and the Chinese medical expert for information transmission;
the analysis module is respectively connected with the user login module, the data storage module and the information transmission module and is used for calculating the diagnosis probability of any expert in the diagnosis records of the consultants so as to judge whether the experts are matched, if the matching criteria are not met, whether the experts in the diagnosis records are matched according to the second judgment of the times of the diagnosis of the same illness state of the consultants in the diagnosis records of the experts, if the matching criteria are not met, the calculated matching parameters of the experts are used as the matching experts of the consultants again, and when the matching parameters do not meet the matching criteria, the matching parameters are calculated and adjusted so as to match the experts.
The records of the consultation of the consultant include, but are not limited to, personal information of the consultant, the condition of the consultation, the time of the consultation, the consultation specialist, the diagnosis results, the treatment scheme, the prescription of the medication, and the like.
More specifically, the system can further comprise a selection module, and the doctor can autonomously select the Chinese medical specialist to make a doctor, so that the doctor experience of the doctor is improved.
According to the intelligent matching method and the intelligent matching system, the intelligent matching of the doctor and the expert is achieved through the AI, so that the accurate matching degree of the doctor and the expert is improved, the doctor experience of the doctor is improved, and meanwhile, the doctor seeing efficiency of the expert is improved.
Specifically, the user login module includes:
the Chinese medicine expert login unit is used for verifying login information of the Chinese medicine expert and connecting the verified Chinese medicine expert with the server;
the doctor registering unit is used for verifying the registering information of the doctor and connecting the doctor passing the verification with the server.
It can be understood by those skilled in the art that the expert of traditional Chinese medicine or the doctor can take the data of the expert of traditional Chinese medicine or the doctor for analysis to match the expert for examination after logging in the server through verification and displaying on-line state.
Specifically, the analysis module calculates the diagnosis probability of any expert in the diagnosis records of the consultant to determine whether to match the expert;
and if the probability of the diagnosis is larger than a second preset probability value, the analysis module judges that the corresponding experts are matched, and the experts with the probability of the diagnosis larger than the second preset probability value are matched according to the descending order of the probability of the diagnosis.
Specifically, the analysis module acquires the visit records of the patients, extracts the visit experts in the visit records, calculates the visit probability of any expert, wherein the visit probability is the ratio of the number of times of the visit of any expert to the total number of times of the visit of the patients, and judges whether the experts are matched according to the visit probability.
The analysis module of the invention aims at any doctor, when expert matching is carried out, firstly, the doctor record of the doctor is taken as a reference, and when the doctor's doctor seeing probability is larger than a second preset probability value, the expert is informed of the state of illness of the doctor, so that the expert can comprehensively know the state of illness and the physical condition of the doctor, the communication efficiency is improved, the accuracy of the expert in treating the state of illness of the doctor is also improved, and the doctor seeing efficiency is further improved.
Specifically, the analysis module compares the diagnosis probability with a first preset probability value under the condition that the calculated diagnosis probability is smaller than or equal to the second preset probability value, and if the diagnosis probability is larger than the first preset probability value, the analysis module extracts the diagnosis times of the same illness state as the doctor in the diagnosis records of the corresponding expert, and secondarily judges whether to match the expert according to the diagnosis times;
the first preset probability value is smaller than the second preset probability value.
Specifically, if the calculated diagnosis probability is smaller than or equal to the second preset probability value, the analysis module primarily judges that the expert is not matched, and compares the diagnosis probability with the first preset probability value to secondarily judge whether the expert is matched or not;
if the probability of the diagnosis is larger than the first preset probability value, the analysis module invokes the diagnosis record of the corresponding expert, extracts the diagnosis times of the same illness state as the person in the diagnosis record, and secondarily judges whether the expert is matched according to the diagnosis times;
the first preset probability value is smaller than the second preset probability value.
According to the invention, the first preset probability value and the second preset probability value are set to represent the degree of understanding of the expert on the illness state of the patient, so that the expert is matched with the patient better, and a better diagnosis effect is realized.
Specifically, the analysis module corrects the diagnosis probability that is greater than the first preset probability value and less than or equal to the second preset probability value according to the extracted diagnosis times, if the corrected diagnosis probability is greater than the second preset probability value, the analysis module judges that the corresponding experts are matched, and matches the experts with the corrected diagnosis probability that is greater than the second preset probability value according to the descending order of the corrected diagnosis probabilities.
Specifically, the analysis module is provided with a plurality of correction coefficients, the analysis module is provided with a plurality of correction modes aiming at the diagnosis probability based on the extracted diagnosis times, and each correction mode corresponds to a different correction coefficient.
Under the condition that the calculated diagnosis probability is smaller than or equal to the second preset probability value, if the diagnosis probability is larger than the first preset probability value, the analysis module indicates that the expert has a certain knowledge on the illness state of the patient, at the moment, the diagnosis probability is corrected according to the diagnosis times of the same illness state of the patient in the diagnosis record of the expert, whether the expert is matched with the secondary judgment is judged according to the corrected diagnosis probability, and the diagnosis experience of the expert on the same illness state is fully considered, so that the accuracy of the expert on the illness state treatment of the patient is improved, and the diagnosis efficiency of the expert is further improved.
Specifically, the analysis module is provided with a first preset number of times of diagnosis and a second preset number of times of diagnosis, the first preset number of times of diagnosis is smaller than the second preset number of times of diagnosis, the analysis module compares the extracted number of times of diagnosis with the first preset number of times of diagnosis and the second preset number of times of diagnosis respectively to select a correction coefficient to correct the probability of diagnosis larger than the first preset probability value,
if the extracted number of times of the examination is smaller than the first preset number of times of the examination, the analysis module judges that the probability of the examination is not corrected;
if the extracted number of times of the diagnosis is greater than or equal to the first preset number of times of the diagnosis and less than the second preset number of times of the diagnosis, the analysis module judges that the first correction coefficient e1 is selected to correct the probability of the diagnosis, and the corrected probability of the diagnosis=the probability of the diagnosis×e1 is set;
if the extracted number of times of the diagnosis is greater than or equal to the second preset number of times of the diagnosis, the analysis module judges that the second correction coefficient e2 is selected to correct the probability of the diagnosis, and the corrected probability of the diagnosis=the probability of the diagnosis×e2 is set;
where 1 < e2 < 1.5, the preferred embodiment is e1=1.2 and e2=1.35.
Specifically, the analysis module determines that no expert is matched when the calculated probability of the diagnosis is equal to or less than the first preset probability value or the corrected probability of the diagnosis is equal to or less than the second preset probability value, calculates a matching parameter of any expert according to the following formula, and sets:
；
wherein F is a matching parameter, T is the expert's visit time, N is the total number of visits by N expert, N is the number of visits by the same illness state as the patient in the total number of visits, T0 is the preset standard visit time, N0 is the preset standard visit total number, N0 is the number of visits by the same illness state as the patient in the preset standard visit total number, alpha, beta, gamma are corresponding weight coefficients, alpha+beta+gamma=1.
As will be appreciated by those skilled in the art, the time of a visit by an expert is the cumulative length of time the expert spends on each visit.
According to the invention, under the condition that the expert's diagnosis probability does not accord with the matching condition, the matching parameter of any expert is calculated, the matching parameter is the characteristic parameter of the expert's matching index relative to the person to be diagnosed, when the expert's total number of times of diagnosis is more, the number of times of diagnosis of the same illness state as the person to be diagnosed is more in the total number of times of diagnosis, and the longer the time of diagnosis is, the stronger the expert's specificity of the disease state to be diagnosed is, the higher the matching degree with the person to be diagnosed is, the diagnosis experience of the person to be diagnosed is improved, and the diagnosis efficiency of the expert is also improved.
Specifically, the analysis module matches the expert according to the matching parameters;
and the analysis module compares the matching parameters with preset matching comparison parameters, and if the matching parameters are larger than the matching comparison parameters, the analysis module matches the experts with the matching parameters larger than the matching comparison parameters according to descending order of the matching parameters.
Specifically, the analysis module determines that the expert is not matched under the condition that the matching parameters are smaller than or equal to the matching comparison parameters, calculates and adjusts the comparison parameters according to the following formula, and sets:
；
wherein Y is an adjustment contrast parameter, C is an expert score, and C0 is a preset standard expert score.
Under the condition that the matching parameters do not accord with the matching conditions, the analysis module calculates the diagnosis probability of the condition of the doctor, which is the same as that of the doctor, in the total times of scoring and the expert diagnosis by the expert, and is used for representing the matching degree of the expert and the doctor.
It will be appreciated by those skilled in the art that after the expert has completed the visit to the consultant, the consultant may score the consultant and the average of the consultant scores is used as the expert score.
Specifically, the analysis module adjusts the matching parameters according to the adjustment comparison parameters, and matches the expert according to the adjusted matching parameters;
the analysis module is provided with a plurality of adjusting coefficients, the analysis module is provided with a plurality of adjusting modes aiming at the matching parameters based on the adjusting comparison parameters, each adjusting mode corresponds to different adjusting coefficients, if the adjusted matching parameters are larger than the matching comparison parameters, the analysis module matches the expert according to descending order arrangement sequences of the adjusted matching parameters, and if the adjusted matching parameters are smaller than or equal to the matching comparison parameters, the analysis module matches the expert according to descending order arrangement sequences of the consultation probability of the expert in the consultation records of the consultation person.
When the adjusted matching parameters are smaller than or equal to the matching comparison parameters, the analysis module indicates that the matching degree of the expert is lower, at the moment, the analysis module performs matching according to the diagnosis probability of the expert in the diagnosis records of the doctor, the expert has a certain knowledge on the illness state of the doctor, and the matching accuracy of doctors and patients can be improved to the greatest extent.
Specifically, a first preset adjustment contrast parameter and a second preset adjustment contrast parameter are arranged in the analysis module, the first preset adjustment contrast parameter is smaller than the second preset adjustment contrast parameter, the analysis module respectively compares the calculated adjustment contrast parameter with the first preset adjustment contrast parameter and the second preset adjustment contrast parameter to select an adjustment coefficient to adjust the matching parameter,
if the calculated adjustment contrast parameter is smaller than a first preset adjustment contrast parameter, the analysis module judges that the first adjustment coefficient f1 is selected for adjusting the matching parameter, and the adjusted matching parameter=the matching parameter multiplied by f1 is set;
if the extracted adjustment contrast parameter is greater than or equal to the first preset adjustment contrast parameter and less than the second preset adjustment contrast parameter, the analysis module judges that the second adjustment coefficient f2 is selected to adjust the matching parameter, and the adjusted matching parameter=the matching parameter multiplied by f2 is set;
if the extracted adjustment contrast parameter is greater than or equal to a second preset adjustment contrast parameter, the analysis module judges that the matching parameter is adjusted by selecting a third adjustment coefficient f3, and the adjusted matching parameter=the matching parameter multiplied by f3 is set;
where 1 < f1 < f2 < f3 < 1.3, f1=1.15, f2=1.2, f3=1.25 are preferred in this embodiment.
Thus far, the technical solution of the present invention has been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of protection of the present invention is not limited to these specific embodiments. Equivalent modifications and substitutions for related technical features may be made by those skilled in the art without departing from the principles of the present invention, and such modifications and substitutions will be within the scope of the present invention.
The foregoing description is only of the preferred embodiments of the invention and is not intended to limit the invention; various modifications and variations of the present invention will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. An AI-based traditional Chinese medicine expert telemedicine assistance system, comprising:
the user login module is used for verifying login information of a user and connecting the verified user with the server, wherein the user comprises a doctor and a Chinese medical expert;
the data storage module comprises a first storage unit for storing the diagnosis records of the patients and a second storage unit for storing the diagnosis records of the Chinese medical specialists;
the information transmission module is used for uploading the illness state data of the doctor to the server and linking the doctor and the Chinese medical expert for information transmission;
the analysis module is respectively connected with the user login module, the data storage module and the information transmission module and is used for calculating the diagnosis probability of any expert in the diagnosis records of the consultants so as to judge whether the experts are matched, if the matching criteria are not met, whether the experts in the diagnosis records are matched according to the second judgment of the times of the diagnosis of the same illness state of the consultants in the diagnosis records of the experts, if the matching criteria are not met, the calculated matching parameters of the experts are used as the matching experts of the consultants again, and when the matching parameters do not meet the matching criteria, the matching parameters are calculated and adjusted so as to match the experts.
2. The AI-based traditional Chinese medical expert telemedicine assistance system of claim 1, wherein the user login module includes:
the Chinese medicine expert login unit is used for verifying login information of the Chinese medicine expert and connecting the verified Chinese medicine expert with the server;
the doctor registering unit is used for verifying the registering information of the doctor and connecting the doctor passing the verification with the server.
3. The AI-based traditional Chinese medical expert telemedicine assistance system of claim 2, wherein the analysis module calculates a probability of a visit by any expert in a visit record of a visit person to determine whether to match the expert;
and if the probability of the diagnosis is larger than a second preset probability value, the analysis module judges that the corresponding experts are matched, and the experts with the probability of the diagnosis larger than the second preset probability value are matched according to the descending order of the probability of the diagnosis.
4. The AI-based traditional Chinese medical expert telemedicine auxiliary system according to claim 3, wherein the analysis module compares the diagnosis probability with a first preset probability value under the condition that the calculated diagnosis probability is smaller than or equal to the second preset probability value, and if the diagnosis probability is larger than the first preset probability value, the analysis module extracts the diagnosis times of the same illness state as the patient in the diagnosis record of the corresponding expert, and secondarily judges whether to match the expert according to the diagnosis times;
the first preset probability value is smaller than the second preset probability value.
5. The AI-based traditional Chinese medical expert telemedicine assistance system of claim 4, wherein the analysis module corrects the visit probability that is greater than the first preset probability value and less than or equal to the second preset probability value according to the extracted number of visits, and if the corrected visit probability is greater than the second preset probability value, the analysis module determines to match the corresponding expert, and matches the experts whose corrected visit probability is greater than the second preset probability value in descending order of the corrected visit probabilities.
6. The AI-based traditional Chinese medical expert telemedicine assistance system of claim 5, wherein the analysis module is provided with a plurality of correction coefficients, the analysis module is provided with a plurality of correction modes aiming at the diagnosis probability based on the extracted diagnosis times, and each correction mode corresponds to a different correction coefficient.
7. The AI-based traditional Chinese medical expert telemedicine assistance system of claim 6, wherein the analysis module determines that no expert is matched when the calculated probability of a visit is equal to or less than the first preset probability value or the corrected probability of a visit is equal to or less than the second preset probability value, and calculates a matching parameter of any expert according to the following formula, and sets:
，
wherein F is a matching parameter, T is the expert's visit time, N is the expert's total number of visits, N is the number of visits of the same illness state as the patient in the total number of visits, T0 is the preset standard visit time, N0 is the preset standard visit total number, N0 is the number of visits of the same illness state as the patient in the preset standard visit total number, and alpha, beta and gamma are corresponding weight coefficients.
8. The AI-based traditional Chinese medical expert telemedicine assistance system of claim 7, wherein the analysis module matches an expert based on the matching parameters;
and the analysis module compares the matching parameters with preset matching comparison parameters, and if the matching parameters are larger than the matching comparison parameters, the analysis module matches the experts with the matching parameters larger than the matching comparison parameters according to descending order of the matching parameters.
9. The AI-based traditional Chinese medicine expert telemedicine assistance system of claim 8, wherein the analysis module determines that no matching is performed on the expert if the matching parameters are all less than or equal to the matching comparison parameters, and calculates the adjustment comparison parameters according to the following formula, and sets:
，
wherein Y is an adjustment contrast parameter, C is an expert score, and C0 is a preset standard expert score.
10. The AI-based traditional Chinese medical expert telemedicine assistance system of claim 9, wherein the analysis module adjusts the matching parameters according to the adjusted comparison parameters and matches the expert according to the adjusted matching parameters;
the analysis module is provided with a plurality of adjusting coefficients, the analysis module is provided with a plurality of adjusting modes aiming at the matching parameters based on the adjusting comparison parameters, each adjusting mode corresponds to different adjusting coefficients, if the adjusted matching parameters are larger than the matching comparison parameters, the analysis module matches the expert according to descending order arrangement sequences of the adjusted matching parameters, and if the adjusted matching parameters are smaller than or equal to the matching comparison parameters, the analysis module matches the expert according to descending order arrangement sequences of the consultation probability of the expert in the consultation records of the consultation person.
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