CN112185503A - Intelligent auxiliary diagnosis system and method for traditional Chinese medicine - Google Patents
Intelligent auxiliary diagnosis system and method for traditional Chinese medicine Download PDFInfo
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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
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
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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
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
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- 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
Abstract
The invention provides a traditional Chinese medicine intelligent auxiliary diagnosis system and method, which comprises a patient client, a data processing end and a doctor client, wherein the patient client is in communication connection with the data processing end, the data processing end is in communication connection with the doctor client, the patient client comprises an inquiry module and a medicine taking feedback information module, the data processing end comprises a cloud database, a basic pathogenesis calculation module, a medicine evidence calculation module, a prescription recommendation module and a prescription matching correction module, and the doctor client comprises a prescription module. The intelligent auxiliary diagnosis system and method for traditional Chinese medicine provided by the invention can cover all processes of disease condition acquisition, calculation analysis, prescription output and data correction, and improves prescription development efficiency and accuracy of traditional Chinese medicine groups through standardized syndrome differentiation and closed-loop correction.
Description
Technical Field
The invention relates to the technical field of health monitoring equipment, in particular to a traditional Chinese medicine intelligent auxiliary diagnosis system and method.
Background
With the improvement of living standard of people, people pay more attention to their health problems, especially under the working pressure of tension and fast pace, the pathological changes of the body are often performed in a subtler way, and therefore, it is especially necessary to have a real-time understanding of their own body conditions.
At present, the traditional Chinese medicine world has a plurality of different system genres, wherein the classical menstruation genre has a plurality of different syndrome differentiation thinking, but the syndrome differentiation thinking is different but has communicated essence, most of the essence of the traditional Chinese medicine world is from the classical menstruation syndrome differentiation system of the holy zhang zhong view of Han dynasty, and the part can be standardized and can realize closed-loop closure by means of a modern means.
The existing diagnosis and treatment system can complete the diagnosis which is asked for, and can not well recommend the warp to the doctor by giving some patient body health indexes, conditioning suggestions and food therapy suggestions at the same time.
Disclosure of Invention
The invention provides a traditional Chinese medicine intelligent auxiliary diagnosis system and method, which can cover all processes of disease condition acquisition, calculation analysis, prescription output and data correction, and improve prescription development efficiency and accuracy of a traditional Chinese medicine group through standardized syndrome differentiation and closed-loop correction.
The invention adopts the following technical scheme:
an intelligent traditional Chinese medicine auxiliary diagnosis system comprises a patient client, a data processing end and a doctor client, wherein the patient client is in communication connection with the data processing end, the data processing end is in communication connection with the doctor client, the patient client is used for filling and submitting a questionnaire or medicine taking feedback information to the data processing end by a patient, the data processing end calculates and outputs a recommended prescription or corrects the prescription matching degree according to the medicine taking feedback information, and the doctor client is used for confirming the prescription calculated and output by the data processing end;
the patient client includes:
the inquiry module is used for filling and submitting an inquiry sheet to the data processing end by the patient;
the medicine taking feedback information module is used for filling and submitting medicine taking feedback information to the data processing terminal after a patient takes medicine, wherein the medicine taking feedback information comprises thorough relief, basic relief, slight relief and unreleased;
the data processing terminal comprises:
the cloud database is used for storing a plurality of prescriptions, each prescription contains a core drug pair, and each prescription has a matching degree;
the basic pathogenesis computing module is used for matching the corresponding basic pathogenesis according to the inquiry sheet submitted by the patient;
the medicine evidence calculation module is used for matching medicines according to basic pathogenesis and obtaining a core medicine pair according to the matched medicines;
the prescription recommending module is used for matching prescriptions in the cloud database according to the core drug pairs and outputting a recommended prescription list according to the prescription matching degree;
the prescription matching correction module is used for correcting the matching degree of the corresponding prescription in the cloud database according to the medicine taking feedback information filled in by the patient;
the doctor client includes:
and the prescription issuing module is used for receiving the questionnaire filled by the patient and sent by the data processing terminal, confirming the recommended prescription list output by the data processing terminal in a matching way and sending the prescription to the patient client.
Further, the basic pathogenesis comprises three types of epitopes, including exterior cluster, exterior cold, stroke, ying damage and essence damage, the taiyin comprises blood damage, blood deficiency, interior cold and water retention, and the yangming comprises interior heat, interior nodes, interior dryness, hydrothermal, exterior heat, exterior nodes and exterior dryness.
Further, the inquiry sheet comprises an epitope symptom and a lining symptom, and the epitope symptom and the lining symptom both comprise a plurality of inquiry choices;
and in the basic pathogenesis computing module, each option in the inquiry selection questions is set to correspond to one basic pathogenesis in one type of basic pathogenesis.
Further, the drug evidence calculation module matches a plurality of drugs according to a plurality of basic pathogenesis, the drugs are combined to form a plurality of drug pairs, and the drug pair of the matched drug with the highest occurrence frequency in the drug pairs is a core drug pair; wherein each underlying pathogenesis corresponds to one or more drugs;
the prescription recommending module arranges the prescriptions from high to low according to the matching degree to form a prescription recommending list according to the plurality of prescriptions containing the core medicine pair in the core medicine pair matching cloud database, and removes the prescription from the prescription recommending list when the matching degree of the prescription is lower than 60%.
Further, in the prescription matching correction module, the method for correcting the prescription matching degree includes: the prescription correction module records the matching times of the prescription recommendation module, the matching degree of the prescription corresponding to thorough relief in the medicine taking feedback information is 100%, the matching degree of the prescription corresponding to basic relief is 80%, the matching degree of the prescription corresponding to slight relief is 60%, and the matching degree of the prescription corresponding to unreleased relief is 0%;
and correcting the original matching degree when the accumulated times reach one hundred, wherein the calculation formula of the corrected matching degree is as follows:
new matching degree (original matching degree multiplied by original cumulative matching times + new matching degree) divided by total cumulative matching times
The new matching degree is the corrected matching degree, the original accumulated matching times are the times of accumulated matching before the current matching, and the original accumulated matching times and the total accumulated matching times both comprise initial matching degrees corresponding to the first input.
The invention also provides an intelligent auxiliary diagnosis method for the traditional Chinese medicine, which comprises the following steps:
s1, filling an inquiry sheet in an inquiry module at the patient input end by the patient, and submitting the inquiry sheet to a data processing end;
s2, the data processing end sends the inquiry sheet to the doctor client;
s3, matching the corresponding basic pathogenesis by the basic pathogenesis computing module of the data processing end according to the inquiry sheet submitted by the patient;
s4, matching medicines according to the basic pathogenesis by a medicine evidence calculation module of the data processing end, and obtaining a core medicine pair according to the matched medicines;
s5, the prescription recommending module of the data processing end matches the prescription in the cloud database according to the core drug pair, and outputs a recommended prescription list according to the matching degree of the prescription;
s6, the data processing end sends the matched prescription list to the corresponding doctor client;
s7, the prescription module of the doctor client receives the patient filled out inquiry sheet and the matched prescription list sent by the data processing end, and the doctor adjusts and confirms the matched prescription according to the requirement according to the patient filled out inquiry sheet;
s8, the doctor sends the confirmed prescription to the patient client;
s9, after the patient takes the medicine, filling medicine taking feedback information through a medicine taking feedback information module of the patient client, and submitting the medicine taking feedback information to a data processing terminal, wherein the medicine taking feedback information comprises thorough relief, basic relief, slight relief and unreleasion;
and S10, the prescription matching correction module of the data processing end corrects the prescription matching degree of the corresponding prescription in the cloud database according to the medicine taking feedback information filled by the patient.
Further, the basic pathogenesis comprises three types of epitopes, including exterior cluster, exterior cold, stroke, ying damage and essence damage, the taiyin comprises blood damage, blood deficiency, interior cold and water retention, and the yangming comprises interior heat, interior nodes, interior dryness, hydrothermal, exterior heat, exterior nodes and exterior dryness.
Further, in step S1, the questionnaire includes an epitope symptom and a lining symptom, and each of the epitope symptom and the lining symptom includes a plurality of questionnaire options;
in step S3, each option in the inquiry questions of the inquiry sheet is set to correspond to one basic pathogenesis of one type of basic pathogenesis.
Further, in step S4, the medical evidence calculation module matches a plurality of medicines according to a plurality of basic pathogenesis, the plurality of medicines are combined to form a plurality of medicine pairs, and the medicine pair of the plurality of medicine pairs including the matched medicine with the highest occurrence frequency is the core medicine pair; wherein each underlying pathogenesis corresponds to one or more drugs;
in step S5, the prescription recommendation module arranges the prescriptions in a high-to-low matching degree to form a prescription recommendation list according to the plurality of prescriptions including the core pair in the core pair matching cloud database, and removes the prescription from the prescription recommendation list when the matching degree of the prescription is lower than 60%.
Further, in step S10, the method for correcting the prescription matching degree includes: the prescription correction module records the matching times of the prescription recommendation module, the matching degree of the prescription corresponding to thorough relief in the medicine taking feedback information is 100%, the matching degree of the prescription corresponding to basic relief is 80%, the matching degree of the prescription corresponding to slight relief is 60%, and the matching degree of the prescription corresponding to unreleased relief is 0%;
and correcting the original matching degree when the accumulated times reach 100 times, wherein the calculation formula of the corrected matching degree is as follows:
new matching degree (original matching degree multiplied by original cumulative matching times + new matching degree) divided by total cumulative matching times
The new matching degree is the corrected matching degree, the original accumulated matching times are the times of accumulated matching before the current matching, and the original accumulated matching times and the total accumulated matching times both comprise initial matching degrees corresponding to the first input.
The invention has the beneficial effects that: provides a standardized classical meridian syndrome differentiation system, and covers all processes of disease condition collection, calculation analysis, prescription output and data correction. Through standardized syndrome differentiation and closed-loop correction, the prescription development efficiency and accuracy of the traditional Chinese medicine group are improved.
Drawings
Fig. 1 is a system block diagram of an intelligent auxiliary diagnosis system of traditional Chinese medicine of the present invention.
Fig. 2 is a system block diagram of a patient client in the present invention.
Fig. 3 is a system block diagram of a data processing terminal in the present invention.
FIG. 4 is a system diagram of a doctor client in the present invention.
FIG. 5 is a schematic diagram of the steps of an intelligent auxiliary diagnosis method of traditional Chinese medicine of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings.
Example one
As shown in fig. 1, the present embodiment provides an intelligent auxiliary diagnosis system for traditional Chinese medicine, which includes a patient client, a data processing terminal, and a doctor client, wherein the patient client is in communication connection with the data processing terminal, the data processing terminal is in communication connection with the doctor client, the patient client is used for filling in and submitting an inquiry sheet or medicine taking feedback information to the data processing terminal, the data processing terminal calculates and outputs a recommended prescription or corrects the prescription matching degree according to the medicine taking feedback information, and the doctor client is used for confirming the prescription calculated and output by the data processing terminal.
As shown in fig. 2, the patient client includes:
the inquiry module is used for filling and submitting an inquiry sheet to the data processing end by the patient; the inquiry list comprises two parts of epitope symptom and internal symptom, and the two parts of epitope symptom and internal symptom both comprise a plurality of inquiry choices.
And the medicine taking feedback information module is used for filling in and submitting the medicine taking feedback information to the data processing terminal after the patient takes the medicine, wherein the medicine taking feedback information comprises four relief degrees of thorough relief, basic relief, slight relief and unreleased relief, and is selected manually by the patient.
As shown in fig. 3, the data processing side includes:
the cloud database is used for storing a plurality of prescriptions, each prescription contains a core drug pair, each prescription has a matching degree, each prescription can be manually input with a matching degree during initial adding, and the matching degree is subsequently corrected along with feedback of a patient.
The basic pathogenesis computing module is used for matching the corresponding basic pathogenesis according to the inquiry sheet submitted by the patient; the basic pathogenesis comprises three types of epitopes, namely Taiyin and Yangming, wherein the epitope comprises surface beam, surface cold, stroke, nutrient injury and essence injury; taiyin including blood impairment, blood deficiency, internal cold and water retention; ③ the yangming comprises interior heat, interior knot, interior dryness, hydrothermal, exterior heat, exterior knot and exterior dryness; each option in the inquiry and diagnosis selection questions is set to correspond to one basic pathogenesis in one type of basic pathogenesis, and therefore the corresponding basic pathogenesis can be obtained according to the option selected by the patient. For example:
the associated matching information is stored in a cloud database, for more comprehensive use, the selection questions in the inquiry list in the inquiry module can be increased, and after the inquiry selection questions are increased, the basic pathogenesis corresponding to the options of the inquiry selection questions are synchronously increased and added into a basic pathogenesis computing module; likewise, the association between the underlying pathogenesis and the drug may also be updated with the patient's feedback.
The medicine evidence calculation module is used for matching medicines according to basic pathogenesis and obtaining a core medicine pair according to the matched medicines; after the patient fills in the inquiry list, a plurality of options in the inquiry list are selected, the options correspond to a plurality of basic pathogenesis, each basic pathogenesis corresponds to one or more medicines, a plurality of medicines are obtained according to the matching of the basic pathogenesis, the medicines are combined randomly to form a plurality of medicine pairs, and the medicine pair containing the matched medicine with the highest occurrence frequency in the medicine pairs is the core medicine pair. For example, when a patient is frightened, has difficulty in falling asleep, sweats when moving, dizziness, poor appetite and cold belly in an inquiry list, the matched basic pathogenesis is epitope (exterior cold, impairment, stroke, exterior beam) and taiyin (interior deficiency and interior cold), and according to the correlation between the medicament and the basic pathogenesis, the medicaments of cassia twig, peony, ginger and licorice with the highest occurrence frequency are obtained, and the core medicament pair comprising the combination of the medicaments is as follows: ramulus Cinnamomi with Glycyrrhrizae radix, radix Paeoniae with Glycyrrhrizae radix, and rhizoma Zingiberis recens with Glycyrrhrizae radix.
And the prescription recommending module is used for arranging the prescriptions according to the matching degree from high to low to form a prescription recommending list and outputting the prescription recommending list for a doctor to refer to according to the plurality of prescriptions containing the core medicine pair in the core medicine pair matching cloud database, and removing the prescription from the prescription recommending list when the matching degree of the prescription is lower than 60%. For example, a prescription containing the above-described core drug pair is: 38 cassia twig decoction, cassia twig xinjia decoction, cassia twig jia kudzuvine root decoction, trichosanthes kirilowii cassia twig decoction and the like are adopted, wherein the matching degree of 29 prescriptions such as Qianjin cassia twig decoction and the like is lower than 60 percent, so a recommended list is not displayed, wherein the cassia twig decoction with the highest recommendation degree can regulate Ying and Wei, tonify stomach and tonify deficiency.
And the prescription matching correction module is used for correcting the prescription matching degree of the corresponding prescription in the cloud database according to the medicine taking feedback information filled by the patient. The method for correcting the matching degree of the prescription comprises the following steps: the prescription correction module records the matching times of the prescription recommendation module, the matching degree of the prescription corresponding to thorough relief in the medicine taking feedback information is 100%, the matching degree of the prescription corresponding to basic relief is 80%, the matching degree of the prescription corresponding to slight relief is 60%, and the matching degree of the prescription corresponding to unreleased relief is 0%;
and correcting the original matching degree when the accumulated times reach 100 times, wherein the calculation formula of the corrected matching degree is as follows:
new matching degree (original matching degree multiplied by original cumulative matching times + new matching degree) divided by total cumulative matching times
The new matching degree is the corrected matching degree, the original accumulated matching times are the accumulated matching times before the current matching, the original accumulated matching times and the total accumulated matching times both comprise manual first-time input, and the input information comprises a prescription and the initial matching degree of the prescription.
As shown in fig. 4, the doctor client includes:
and the prescription issuing module is used for receiving the questionnaire filled by the patient and sent by the data processing terminal, confirming the recommended prescription list output by the data processing terminal in a matching way and sending the prescription to the patient client.
Example two
As shown in fig. 5, the present embodiment provides an intelligent auxiliary diagnosis method for traditional Chinese medicine, which includes the following steps:
s1, filling an inquiry sheet in an inquiry module at the input end of the patient by the patient, and submitting the inquiry sheet to a data processing end, wherein the inquiry sheet comprises an epitope symptom and a lining symptom, and the epitope symptom and the lining symptom both comprise a plurality of inquiry choice questions.
And S2, the data processing end sends the inquiry sheet to the doctor client.
S3, the basic pathogenesis computing module of the data processing end matches the corresponding basic pathogenesis according to the inquiry list submitted by the patient. The basic pathogenesis comprises three types of epitopes, namely Taiyin and Yangming, wherein the epitope comprises surface beam, surface cold, stroke, nutrient injury and essence injury; taiyin including blood impairment, blood deficiency, internal cold and water retention; ③ the yangming comprises interior heat, interior knot, interior dryness, hydrothermal, exterior heat, exterior knot and exterior dryness; each option in the question is set to correspond to one basic pathogenesis of one type of basic pathogenesis, so that the corresponding basic pathogenesis can be displayed according to the option selected by the patient, as shown in the table in the first embodiment.
S4, matching the medicines according to the basic pathogenesis by the medicine evidence calculation module of the data processing end, and obtaining a core medicine pair according to the matched medicines. The medicine evidence calculation module matches a plurality of medicines according to a plurality of basic pathogenesis, the medicines are combined to form a plurality of medicine pairs, and the medicine pair with the highest occurrence frequency of the matched medicines in the medicine pairs is a core medicine pair; wherein each underlying pathogenesis corresponds to one or more drugs.
S5, the prescription recommending module of the data processing end matches prescriptions in the cloud database according to the core drug pairs, and outputs a recommended prescription list according to the prescription matching degree, wherein each prescription in the cloud database has one prescription matching degree. The prescription recommending module arranges the prescriptions from high to low according to the matching degree to form a prescription recommending list according to the plurality of prescriptions containing the core medicine pair in the core medicine pair matching cloud database, and removes the prescription from the prescription recommending list when the matching degree of the prescription is lower than 60%.
And S6, the data processing end sends the matched recommended prescription list to the corresponding doctor client.
And S7, the prescription module of the doctor client receives the questionnaire filled by the patient and the matched prescription list sent by the data processing terminal, and the doctor adjusts and confirms the matched prescription according to the questionnaire filled by the patient.
And S8, the doctor sends the confirmed prescription to the patient client.
And S9, after the patient takes the medicine, filling medicine taking feedback information through a medicine taking feedback information module of the patient client, and submitting the medicine taking feedback information to the data processing terminal, wherein the medicine taking feedback information comprises thorough relief, basic relief, slight relief and unreleasing.
And S10, the prescription matching correction module of the data processing end corrects the prescription matching degree of the corresponding prescription in the cloud database according to the medicine taking feedback information filled by the patient. The method for correcting the matching degree of the prescription comprises the following steps: the prescription correction module records the matching times of the prescription recommendation module, the matching degree of the prescription corresponding to thorough relief in the medicine taking feedback information is 100%, the matching degree of the prescription corresponding to basic relief is 80%, the matching degree of the prescription corresponding to slight relief is 60%, and the matching degree of the prescription corresponding to unreleased relief is 0%;
and correcting the original matching degree when the accumulated times reach 100 times, wherein the calculation formula of the corrected matching degree is as follows:
new matching degree (original matching degree multiplied by original cumulative matching times + new matching degree) divided by total cumulative matching times
The new matching degree is the corrected matching degree, the original accumulated matching times are the accumulated matching times before the current matching, the original accumulated matching times and the total accumulated matching times both comprise manual first-time input, and the input information comprises a prescription and the initial matching degree of the prescription.
The invention provides a standardized classical meridian syndrome differentiation system, which covers all processes of disease condition acquisition, calculation analysis, prescription output and data correction. Through standardized syndrome differentiation and closed-loop correction, the prescription development efficiency and accuracy of the traditional Chinese medicine group are improved.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those skilled in the art; the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; these modifications and substitutions do not cause the essence of the corresponding technical solution to depart from the scope of the technical solution of the embodiments of the present invention, and are intended to be covered by the claims and the specification of the present invention.
Claims (10)
1. The traditional Chinese medicine intelligent auxiliary diagnosis system is characterized by comprising a patient client, a data processing end and a doctor client, wherein the patient client is in communication connection with the data processing end, the data processing end is in communication connection with the doctor client, the patient client is used for filling and submitting an inquiry sheet or medicine taking feedback information to the data processing end by a patient, the data processing end calculates and outputs a recommended prescription or corrects the matching degree of the prescription according to the medicine taking feedback information, and the doctor client is used for confirming the prescription calculated and output by the data processing end;
the patient client includes:
the inquiry module is used for filling and submitting an inquiry sheet to the data processing end by the patient;
the medicine taking feedback information module is used for filling and submitting medicine taking feedback information to the data processing terminal after a patient takes medicine, wherein the medicine taking feedback information comprises thorough relief, basic relief, slight relief and unreleased;
the data processing terminal comprises:
the cloud database is used for storing a plurality of prescriptions, each prescription contains a core drug pair, and each prescription has a matching degree;
the basic pathogenesis computing module is used for matching the corresponding basic pathogenesis according to the inquiry sheet submitted by the patient;
the medicine evidence calculation module is used for matching medicines according to basic pathogenesis and obtaining a core medicine pair according to the matched medicines;
the prescription recommending module is used for matching prescriptions in the cloud database according to the core drug pairs and outputting a recommended prescription list according to the prescription matching degree;
the prescription matching correction module is used for correcting the matching degree of the corresponding prescription in the cloud database according to the medicine taking feedback information filled in by the patient;
the doctor client includes:
and the prescription issuing module is used for receiving the questionnaire filled by the patient and sent by the data processing terminal, confirming the recommended prescription list output by the data processing terminal in a matching way and sending the prescription to the patient client.
2. The system of claim 1, wherein the basic pathogenesis comprises three categories of epitope, taiyin and yangming, the epitope comprises surface bunch, exterior cold, stroke, impairment of ying and semen, the taiyin comprises impairment of blood, blood deficiency, internal cold and water retention, and the yangming comprises internal heat, internal nodes, internal dryness, hydrothermal process, external heat, external nodes and external dryness.
3. The intelligent auxiliary traditional Chinese medicine diagnosis system according to claim 2, wherein the questionnaire comprises an epitope symptom and a lining symptom, and both the epitope symptom and the lining symptom comprise a plurality of questions for diagnosis selection;
and in the basic pathogenesis computing module, each option in the inquiry selection questions is set to correspond to one basic pathogenesis in one type of basic pathogenesis.
4. The intelligent auxiliary traditional Chinese medicine diagnosis system according to claim 3, wherein the medical evidence calculation module matches a plurality of medicines according to a plurality of basic pathogenesis, the plurality of medicines are combined to form a plurality of medicine pairs, and the medicine pair of the matched medicine with the highest occurrence frequency in the plurality of medicine pairs is a core medicine pair; wherein each underlying pathogenesis corresponds to one or more drugs;
the prescription recommending module arranges the prescriptions from high to low according to the matching degree to form a prescription recommending list according to the plurality of prescriptions containing the core medicine pair in the core medicine pair matching cloud database, and removes the prescription from the prescription recommending list when the matching degree of the prescription is lower than 60%.
5. The intelligent auxiliary traditional Chinese medicine diagnosis system according to claim 1, wherein in the prescription matching correction module, the method for correcting the prescription matching degree comprises: the prescription correction module records the matching times of the prescription recommendation module, the matching degree of the prescription corresponding to thorough relief in the medicine taking feedback information is 100%, the matching degree of the prescription corresponding to basic relief is 80%, the matching degree of the prescription corresponding to slight relief is 60%, and the matching degree of the prescription corresponding to unreleased relief is 0%;
and correcting the original matching degree when the accumulated times reach one hundred, wherein the calculation formula of the corrected matching degree is as follows:
new matching degree (original matching degree multiplied by original cumulative matching times + new matching degree) divided by total cumulative matching times
The new matching degree is the corrected matching degree, the original accumulated matching times are the times of accumulated matching before the current matching, and the original accumulated matching times and the total accumulated matching times both comprise initial matching degrees corresponding to the first input.
6. An intelligent auxiliary diagnosis method for traditional Chinese medicine is characterized by comprising the following steps:
s1, filling an inquiry sheet in an inquiry module at the patient input end by the patient, and submitting the inquiry sheet to a data processing end;
s2, the data processing end sends the inquiry sheet to the doctor client;
s3, matching the corresponding basic pathogenesis by the basic pathogenesis computing module of the data processing end according to the inquiry sheet submitted by the patient;
s4, matching medicines according to the basic pathogenesis by a medicine evidence calculation module of the data processing end, and obtaining a core medicine pair according to the matched medicines;
s5, the prescription recommending module of the data processing end matches the prescription in the cloud database according to the core drug pair, and outputs a recommended prescription list according to the matching degree of the prescription;
s6, the data processing end sends the matched prescription list to the corresponding doctor client;
s7, the prescription module of the doctor client receives the patient filled out inquiry sheet and the matched prescription list sent by the data processing end, and the doctor adjusts and confirms the matched prescription according to the requirement according to the patient filled out inquiry sheet;
s8, the doctor sends the confirmed prescription to the patient client;
s9, after the patient takes the medicine, filling medicine taking feedback information through a medicine taking feedback information module of the patient client, and submitting the medicine taking feedback information to a data processing terminal, wherein the medicine taking feedback information comprises thorough relief, basic relief, slight relief and unreleasion;
and S10, the prescription matching correction module of the data processing end corrects the prescription matching degree of the corresponding prescription in the cloud database according to the medicine taking feedback information filled by the patient.
7. The intelligent auxiliary diagnosis method for traditional Chinese medicine according to claim 6, wherein the basic pathogenesis comprises three categories of epitope, taiyin and yangming, the epitope comprises surface bunch, exterior cold, stroke, impairment of ying and semen, the taiyin comprises impairment of blood, blood deficiency, internal cold and water retention, and the yangming comprises internal heat, internal nodes, internal dryness, hydrothermal method, external heat, external nodes and external dryness.
8. The intelligent auxiliary diagnosis method of traditional Chinese medicine according to claim 7,
in step S1, the inquiry sheet includes an epitope symptom and a lining symptom, and both the epitope symptom and the lining symptom include a plurality of inquiry choices;
in step S3, each option in the inquiry questions of the inquiry sheet is set to correspond to one basic pathogenesis of one type of basic pathogenesis.
9. The intelligent auxiliary diagnosis method of traditional Chinese medicine according to claim 8,
in step S4, the medical evidence calculation module matches a plurality of medicines according to a plurality of basic pathogenesis, the plurality of medicines are combined to form a plurality of medicine pairs, and the medicine pair of the plurality of medicine pairs including the matched medicine with the highest occurrence frequency is a core medicine pair; wherein each underlying pathogenesis corresponds to one or more drugs;
in step S5, the prescription recommendation module arranges the prescriptions in a high-to-low matching degree to form a prescription recommendation list according to the plurality of prescriptions including the core pair in the core pair matching cloud database, and removes the prescription from the prescription recommendation list when the matching degree of the prescription is lower than 60%.
10. The intelligent auxiliary diagnosis method of traditional Chinese medicine according to claim 8,
in step S10, the method for correcting the prescription matching degree includes: the prescription correction module records the matching times of the prescription recommendation module, the matching degree of the prescription corresponding to thorough relief in the medicine taking feedback information is 100%, the matching degree of the prescription corresponding to basic relief is 80%, the matching degree of the prescription corresponding to slight relief is 60%, and the matching degree of the prescription corresponding to unreleased relief is 0%;
and correcting the original matching degree when the accumulated times reach 100 times, wherein the calculation formula of the corrected matching degree is as follows:
new matching degree (original matching degree multiplied by original cumulative matching times + new matching degree) divided by total cumulative matching times
The new matching degree is the corrected matching degree, the original accumulated matching times are the times of accumulated matching before the current matching, and the original accumulated matching times and the total accumulated matching times both comprise initial matching degrees corresponding to the first input.
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