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A method for predicting the incompatibility of traditional Chinese medicine based on supervised learning framework

A technology of incompatibility and supervised learning, applied in the fields of drugs or prescriptions, informatics, medical informatics, etc., can solve the problems of inability to predict contraindications, huge costs, adverse drug reactions, etc. The effect of high accuracy and reduced subjectivity

Active Publication Date: 2022-04-22
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

A medical experiment method that is effective for a certain incompatibility is not applicable to other incompatibility, so the method based on medical experiment is not universal
[0010] (2) Based on the medical experiment method, the operation process is complicated, the experiment costs a lot of money, and it also consumes manpower and material resources, and has great limitations
They cannot predict contraindication relationships between unknown drugs
However, there are a large number of traditional Chinese medicines, and any combination of two medicines may produce adverse drug reactions.

Method used

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  • A method for predicting the incompatibility of traditional Chinese medicine based on supervised learning framework
  • A method for predicting the incompatibility of traditional Chinese medicine based on supervised learning framework
  • A method for predicting the incompatibility of traditional Chinese medicine based on supervised learning framework

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0131] In the process of predicting the incompatibility of traditional Chinese medicine, predict whether there is incompatibility between iron and Dihuang.

[0132] Firstly, extract the efficacy and taste properties of iron and earth yellow in the "Dictionary of Chinese Medicine" as follows:

[0133] 1) Efficacy attributes:

[0134] Iron: calming the liver, suppressing convulsions, detoxifying, suppressing sores, nourishing blood

[0135] Dihuang: heat-clearing, nourishing yin, nourishing blood, regulating dredging, nourishing yin, cooling blood

[0136] 2) Sex and taste attributes:

[0137] Iron: cool, pungent

[0138] Dihuang: slightly cold, sweet, bitter

[0139] If taboo threshold I min =0.600., then the attributes of iron and Dihuang are input into the Chinese medicine incompatibility prediction model respectively, and the calculated incompatibility score is 0.784, which is greater than the threshold I min . Therefore, it is predicted that there is a compatibility ...

Embodiment 2

[0141] Table 1: The symbols and their meanings mainly involved in the present invention

[0142]

Embodiment 3

[0143] Example 3: The implicit relationship between drug attributes and incompatibility

[0144] In the study of traditional Chinese medicine drug pairs, it was found that drugs with similar properties usually have synergistic effects. Based on this research conclusion, the present invention puts forward the hypothesis that "drugs constituting incompatibility usually have dissimilar attributes", and conducts statistical tests on efficacy, property and taste respectively to verify the above hypothesis.

[0145] Hypothesis 1: Incompatible drugs have dissimilar efficacy, i.e. satisfy

[0146] sim e (h i , h j )e (h k , h l ), Y ij =Y ji =1,Y kl =Y lk =0,

[0147] where (h i , h j ) is an incompatible drug pair, (h k , h l ) is an incompatible drug pair, sim e (h i , h j ) = U(i,;) U(j,;) T Indicates incompatible drug pairs (h i , h j ) Chinese medicine h i and h j Similarity of efficacy, sim e (h k , h l ) = U(k,;) U(l,;) T Indicates the incompatible dru...

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Abstract

The invention belongs to the technical field of traditional Chinese medicine compatibility data mining, and discloses a method for predicting Chinese medicine compatibility taboos based on a supervised learning framework. Firstly, data on compatibility taboos and drug attributes are collected, a basic learning model for compatibility taboos is constructed, and the relationship between drug attributes and Chinese medicine compatibility taboos is verified. The implicit relationship among them is extracted from the classic ancient books as the supervision information of the model; then the basic model and constraint items are combined to construct a Chinese medicine incompatibility learning model, and the model parameters are optimized; finally, the model is used to predict the incompatibility relationship. The invention can model the incompatibility relationship between medicines, and constructs a Chinese medicine incompatibility learning model by introducing the efficacy of medicines, properties of nature and taste, and the relationship between the attributes. The invention reveals the relationship of incompatibility of traditional Chinese medicines from a new angle, greatly reduces the space for medical experiments, and improves the efficiency of identification of incompatibility.

Description

technical field [0001] The invention belongs to the technical field of traditional Chinese medicine compatibility mining, and in particular relates to a method for predicting Chinese medicine compatibility taboos based on a supervised learning framework. Background technique [0002] At present, the existing technologies commonly used in the industry are as follows: [0003] Traditional Chinese medicine is a precious wealth created by the Chinese nation for five thousand years, and has made great contributions to the prosperity of the nation. It has a complete and systematic theoretical system. The compatibility of traditional Chinese medicine prescriptions is an important means of TCM treatment. As the core of TCM treatment, it embodies the laws of TCM treatment. [0004] The "seven emotions" proposed in "Shen Nong's Materia Medica" is the general outline of the compatibility theory of traditional Chinese medicine, which refers to seven aspects of the compatibility relatio...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G16H50/70G16H20/13
CPCG16H50/70G16H20/13
Inventor 李巧勤刘勇国杨尚明朱嘉静张云肖迪尹傅翀
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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