CN111816305A - Cold Chinese patent medicine recommendation method based on artificial intelligence - Google Patents
Cold Chinese patent medicine recommendation method based on artificial intelligence Download PDFInfo
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- CN111816305A CN111816305A CN202010775295.5A CN202010775295A CN111816305A CN 111816305 A CN111816305 A CN 111816305A CN 202010775295 A CN202010775295 A CN 202010775295A CN 111816305 A CN111816305 A CN 111816305A
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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
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- 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
- G16H20/90—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to alternative medicines, e.g. homeopathy or oriental medicines
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Abstract
The invention discloses an artificial intelligence based cold Chinese patent medicine recommendation method, which comprises the following steps: expert medical record entry, neural network training, neural network prediction and Chinese patent medicine medication recommendation. The method creatively provides 29 human body characteristics, and different conditions of each characteristic are represented by numbers 0,1,2,3 and 4, so that dialectical medication experience of Chinese medicine experts can be converted into a digital form, then deep neural network training is carried out, and finally a prediction result is given, so that a higher-level dialectical medication suggestion of the Chinese patent medicine can be given to a patient, the dialectical medication level of the Chinese medicine of a western pharmacist can be improved, and the phenomenon of misuse and abuse of the Chinese patent medicine can be greatly improved.
Description
Technical Field
The invention relates to the technical field of medicines, in particular to an artificial intelligence-based recommendation method for patent medicines in cold.
Background
Common cold is a common disease in life and can occur all the year round. The winter and spring are high-incidence seasons of influenza every year, all hospitals are always full of the influenza, and emergency patients who queue to see cold and fever late are more frequent.
The traditional Chinese medicine is a treasure of Chinese civilization. In a long history process, China has a lot of times of plagues, and the traditional Chinese medicine plays an irreplaceable role in preventing and treating influenza. The Chinese patent medicine is prepared into a preparation form with a certain specification according to a specified prescription and standard by taking Chinese herbal pieces as raw materials under the guidance of the theory of traditional Chinese medicine. The Chinese patent medicine has the characteristics of obvious curative effect, convenient administration and the like, and is more and more widely applied clinically. Chinese medicine treatment schemes are thoroughly introduced in an epidemic common cold diagnosis and treatment scheme (2019 edition) issued by the Wei-Jian Commission of China; many Chinese patent medicines such as Huoxiang Zhengqi liquid, Jinhua Qinggan granule, Lianhua Qingwen Capsule, and Shufeng Jiedu Capsule are also recorded in the "diagnosis and treatment of pneumonia caused by New coronavirus infection". Therefore, the Chinese patent medicine has obvious curative effect on the exogenous diseases such as cold, flu, even novel early mild coronavirus and the like.
According to the statistical data of the Chinese over-the-counter drug association, the cold is the highest self-diagnosis and treatment ratio of the common diseases in China at present, and the first choice for treating a plurality of cold patients is to buy the drugs by themselves in a pharmacy. However, most pharmacists in pharmacists are western pharmacists, and the dialectical theory of traditional Chinese medicine and the professional knowledge of traditional Chinese medicine are not strict and comprehensive, and in addition, most pharmacists in pharmacy recommend highly proficient Chinese patent medicines for the reasons of their own benefits and the like, so most common patients have difficulty in obtaining a real traditional Chinese medicine dialectical treatment scheme.
Therefore, it is a difficult point to get a dialectical treatment plan as high as that of a traditional Chinese medicine specialist in a pharmacy for more common patients to buy Chinese patent medicines.
Disclosure of Invention
1. Technical problem to be solved
The invention solves the technical problem that the Chinese patent medicine has obvious effect of treating the cold on the premise of dialectical medication, but most of the current common patients buy the Chinese patent medicine by themselves or in a pharmacy, so that higher-level traditional Chinese medicine dialectical treatment is difficult to obtain. The cold Chinese patent medicine recommendation method based on artificial intelligence is provided, the physical condition of a patient can be fully acquired, the problem that the traditional Chinese medicine dialectical experience of pharmacist western medicine is insufficient is solved, and the cold cure rate of the patient is improved.
2. Technical scheme
In order to achieve the purpose, the invention provides the following technical scheme: an artificial intelligence based cold Chinese patent medicine recommendation method comprises the following steps:
step 1, classifying the physical condition of a patient according to 29 different characteristics, coding attN (N is 1, 2.., 29), and simultaneously inputting basic information of the patient;
step 2, representing each physical condition characteristic of the step 1 by using numbers 0,1,2,3,4,5,. and the like according to different conditions or degrees, and then forming a digital characteristic index attN of the complete physical condition of the patient (N is 1,2,. once, 29, N is 0,1,2,3,4,5,. once);
step 3, encoding medT (T ═ 1, 2..) for the common cold Chinese patent medicine sold in the market, and storing information of functional indication, avoiding crowd, price and the like of the corresponding cold Chinese patent medicine;
step 4, inputting medical plan data of medicine taking based on syndrome differentiation of a traditional Chinese medicine expert, and enabling a digitalized characteristic index attN to correspond to a Chinese patent medicine code medT, namely { attN: n, attN: n, attN: n, } - > (result: medT };
step 5, establishing an artificial neural network with digitized characteristics attN as an input layer and Chinese patent medicine codes medT as an output layer, and training medical record data recorded in the step 4;
step 6, establishing an artificial neural network model by using the training result of the step 5, and predicting according to 29 physical condition characteristics attN of the step 1 to obtain a Chinese patent medicine recommendation result;
and 7, comparing the Chinese patent medicine recommendation result in the step 6 with the basic information of the patient in the step 1 to obtain a final Chinese patent medicine result.
The recommended method for the cold Chinese patent medicine based on artificial intelligence is characterized in that the 29 physical condition characteristics attN comprise fever, aversion to cold (aversion to cold), aversion to heat, perspiration and perspiration, aversion to wind, head, complexion, thirst, throat, nasal discharge, eyes, dry mouth and bitter taste, cough, cold hands and feet, dysphoria, body pain or not, mental state, sleeping, eating condition, vomiting condition, stomach, chest, abdomen, urine, excrement, tongue shape, tongue fur, tongue quality and tongue wetness.
In the method for recommending Chinese patent medicine for treating cold based on artificial intelligence, the artificial neural network is a three-layer neural network, and the number of hidden nodes is 10.
The cold Chinese patent medicine recommendation method based on artificial intelligence is characterized in that the basic information of the patient comprises name, sex, age, height, weight and allergy history.
3. Advantageous effects
In conclusion, the beneficial effects of the invention are as follows:
(1) the cold Chinese patent medicine recommendation method can give the patient a medicine taking suggestion based on traditional Chinese medicine syndrome differentiation through artificial neural network training and prediction, improve the level of medicine taking in a drugstore based on syndrome differentiation, greatly improve the phenomenon of misuse and abuse of Chinese patent medicines and improve the cure rate of cold;
(2) the cold Chinese patent medicine recommendation method disclosed by the invention has the advantages that the physical conditions of the patients are expressed by 29 different characteristics, so that data support can be provided for differential medication of traditional Chinese medicine comprehensively, and the phenomenon that the current pharmacy only inquires about partial physical conditions of the patients is avoided.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
An artificial intelligence based cold Chinese patent medicine recommendation method comprises the following steps:
step 1, classifying the physical condition of a patient according to 29 different features, coding attN (N ═ 1, 2.., 29), and simultaneously inputting basic information of the patient:
the 29 physical conditions included: fever, aversion to cold (aversion to cold), aversion to heat, sweating and absence of sweat, aversion to wind, head, complexion, thirst condition, pharynx, nasal discharge, eyes, dry mouth and bitter taste, cough, cold hands and feet, dysphoria, body pain or not, mental state, sleep, eating condition, vomiting condition, stomach, chest, abdomen, urine, stool, tongue shape, tongue coating, tongue texture, tongue moistness;
the basic information includes name, gender, age, height, weight and allergy history.
Step 2, each physical condition characteristic of step 1 is represented by the numbers 0,1,2,3,4,5,. and the like according to different conditions or degrees, and then a digitalized characteristic index attN of the complete physical condition of the patient is formed (N is 1,2,...,29, N is 0,1,2,3, 4.):
for example:
and 3, encoding a medT (T1, 2.) for a common cold Chinese patent medicine sold in the market, and storing information of the corresponding cold Chinese patent medicine, such as functional indications, avoided crowds, price and the like:
step 4, inputting medical plan data after syndrome differentiation of traditional Chinese medicine, and corresponding the digital characteristic index attN: n to the Chinese patent medicine code medT, namely { attN: n, attN: n, attN: n, } - > (result: medT }:
symptoms such as wind-cold type of common cold: fever, cold feeling, nasal discharge and no sweat, and can be used for treating wind-cold type common cold
The fact that the dialectical experience of the characters can be converted into digital storage is that:
{att1:2,att2:2,att3:0,att4:0,……}->{result:med1}
such as influenza symptoms: red face, high fever, headache, thirst, sore throat, joint pain, yellow urine, and yellow and greasy tongue coating can be used for treating infectious diseases with LIANHUAQINGWEN Capsule,
the fact that the dialectical experience of the characters can be converted into digital storage is that:
{att1:2,att2:0,att3:0,att4:0,……}->{result:med7}
further symptoms such as cold: fever, cold intolerance, aversion to cold, vomiting, diarrhea, and diarrhea, white, thick and greasy tongue coating, and can be treated by Huoxiang Zhengqi liquid or capsule,
the fact that the dialectical experience of the characters can be converted into digital storage is that:
{att1:2,att2:2,att3:0,att4:0,……}->{result:med9}
step 5, establishing an artificial neural network with digitized characteristics attN as an input layer and Chinese patent medicine codes medT as an output layer, and training medical record data recorded in the step 4;
step 6, establishing an artificial neural network model by using the training result of the step 5, and predicting according to 29 physical condition characteristics attN of the step 1 to obtain a Chinese patent medicine recommendation result;
and 7, comparing the Chinese patent medicine recommendation result in the step 6 with the basic information of the patient in the step 1 to obtain a final Chinese patent medicine result.
Preferably, the artificial neural network is a three-layer neural network, and the number of hidden nodes is 10.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (4)
1. An artificial intelligence based cold Chinese patent medicine recommendation method is characterized by comprising the following steps:
step 1, classifying the physical condition of a patient according to 29 different characteristics, coding attN (N is 1, 2.., 29), and simultaneously inputting basic information of the patient;
step 2, representing each physical condition characteristic of the step 1 by using numbers 0,1,2,3,4,5,. and the like according to different conditions or degrees, and then composing a digital characteristic index attN of the complete physical condition of the patient (N is 1,2,...,29, N is 0,1,2,3,4, 5.);
step 3, encoding medT (T ═ 1, 2..) for the common cold Chinese patent medicine sold in the market, and storing information of functional indication, avoiding crowd, price and the like of the corresponding cold Chinese patent medicine;
step 4, inputting medical plan data of medicine taking based on syndrome differentiation of a traditional Chinese medicine expert, and enabling a digitalized characteristic index attN to correspond to a Chinese patent medicine code medT, namely { attN: n, attN: n, attN: n, } - > (result: medT };
step 5, establishing an artificial neural network with digitized characteristics attN as an input layer and Chinese patent medicine codes medT as an output layer, and training medical record data recorded in the step 4;
step 6, establishing an artificial neural network model by using the training result of the step 5, and predicting according to 29 physical condition characteristics attN of the step 1 to obtain a Chinese patent medicine recommendation result;
and 7, comparing the Chinese patent medicine recommendation result in the step 6 with the basic information of the patient in the step 1 to obtain a final Chinese patent medicine result.
2. The recommended method for a Chinese patent drug for cold based on artificial intelligence of claim 1, wherein the 29 physical characteristics attN include fever, chilliness (aversion to cold), aversion to heat, sweatiness, aversion to wind, head, complexion, thirst, throat, nasal discharge, eyes, dry mouth, bitter taste, cough, cold hands and feet, emotional irritability, body pain, mental state, sleep, eating, vomiting, stomach, chest, abdomen, urine, stool, tongue shape, tongue coating, tongue texture, and tongue wetness.
3. The artificial intelligence-based cold Chinese patent medicine recommendation method according to claim 1, wherein the artificial neural network is a three-layer neural network, and the number of hidden layer nodes is 10 layers.
4. The artificial intelligence based cold Chinese patent medicine recommendation method as claimed in claim 1, wherein the patient basic information includes name, gender, age, height, weight and allergy history.
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| CN202010775295.5A CN111816305A (en) | 2020-08-05 | 2020-08-05 | Cold Chinese patent medicine recommendation method based on artificial intelligence |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112667922A (en) * | 2021-01-12 | 2021-04-16 | 山东大学 | Novel coronavirus traditional Chinese medicine formula recommendation method and system based on collaborative filtering |
| CN113140281A (en) * | 2021-03-29 | 2021-07-20 | 华中科技大学同济医学院附属协和医院 | Management method and management system for chemotherapy medication of hematological tumor patient |
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Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2003030327A (en) * | 2001-07-16 | 2003-01-31 | Data Index Kk | Medicine retrieval system |
| CN101308525A (en) * | 2007-05-15 | 2008-11-19 | 深圳市天信生物科技有限公司 | OTC self-help medicine-selecting method and system |
| CN109166619A (en) * | 2018-07-20 | 2019-01-08 | 上海溯斋网络科技有限公司 | Chinese medicine intelligent diagnostics auxiliary system and method based on neural network algorithm |
| CN109087691A (en) * | 2018-08-02 | 2018-12-25 | 科大智能机器人技术有限公司 | A kind of OTC drugs recommender system and recommended method based on deep learning |
| CN109285605A (en) * | 2018-09-11 | 2019-01-29 | 青岛农业大学 | A kind of medical diagnosis system and diagnostic method based on artificial intelligence |
Non-Patent Citations (3)
| Title |
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| 中华中医药学会肺系病专业委员会: "普通感冒中医证候诊断标准(2013版)", 《中医杂志》 * |
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| 无: "流行性感冒", 《河北中医》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112667922A (en) * | 2021-01-12 | 2021-04-16 | 山东大学 | Novel coronavirus traditional Chinese medicine formula recommendation method and system based on collaborative filtering |
| CN113140281A (en) * | 2021-03-29 | 2021-07-20 | 华中科技大学同济医学院附属协和医院 | Management method and management system for chemotherapy medication of hematological tumor patient |
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Application publication date: 20201023 |