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Adverse drug reaction mining method and system

A technology of adverse reactions and drugs, applied in medical data mining, special data processing applications, instruments, etc., can solve the problems of not doing in-depth research, staying in adverse drug reactions, and being unable to effectively reduce adverse reactions, so as to reduce the incidence risk effect

Inactive Publication Date: 2016-10-26
BEIJING QUALITY & ZEAL INFORMATION TECH CO LTD
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AI Technical Summary

Problems solved by technology

However, the research on adverse drug reactions in various countries is still at the level of mathematical statistical analysis in a general sense, and no in-depth research has been done.
The current research methods on adverse drug reactions in my country focus more on the frequency of adverse drug reactions, which cannot effectively reduce the risk of adverse drug reactions during clinical medication

Method used

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  • Adverse drug reaction mining method and system
  • Adverse drug reaction mining method and system
  • Adverse drug reaction mining method and system

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Embodiment Construction

[0052] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and embodiments. The following examples are intended to illustrate the present invention, but not to limit the scope of the present invention.

[0053] The embodiments of the present invention are based on the local and global consistency learning (Learning with local and global consistency) algorithm for mining adverse drug reactions. Before introducing the details of the embodiments of the present invention in detail, some concepts and steps of the local-global consistency learning algorithm are briefly described.

[0054] The local-global consistency learning algorithm is a graph-based semi-supervised learning algorithm. It is a non-parametric, direct inference, and discriminative machine learning algorithm with good classification performance. Its basic principle is: construct a graph according to the similarity between data, then ...

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Abstract

The present invention discloses an adverse drug reaction mining method and system. According to the method, a drug topology similarity matrix and an adverse reaction topology similarity matrix are constructed, global correlation degree vectors of drug and adverse reaction combinations are calculated according to the drug topology similarity matrix and the adverse reaction topology similarity matrix, all characteristic vectors of the drug and adverse reaction combinations are calculated according to similarity of the global correlation degree vectors, by utilization of a learning algorithm with local and global consistency, characteristic vectors of known drug and adverse reaction combinations and characteristic vectors of drug and adverse reaction combinations having the similarity greater than a preset value are classified so as to determine whether unknown drug and adverse reaction combinations have corresponding relationships, so that risks of clinical adverse drug reaction are reduced.

Description

technical field [0001] The invention relates to the technical field of data mining, in particular to a method and system for mining adverse drug reactions. Background technique [0002] With the rapid development of the pharmaceutical industry, a large number of drugs continue to emerge and are widely used, and the subsequent consequence is that the number of adverse drug reactions has risen sharply, which has brought damage to the physical and mental health of patients. Adverse drug reactions refer to the harmful and unexpected reactions of drugs under normal usage and dosage for prevention, diagnosis, treatment or regulation of physiological functions. According to the statistics of the World Health Organization (WHO), the proportion of adverse drug reactions caused by taking drugs in various countries in the world is about 10% to 30%. Every year, more than 5 million people are hospitalized due to adverse drug reactions, and the number of deaths due to adverse drug reactio...

Claims

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Application Information

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IPC IPC(8): G06F19/00
CPCG16H50/70
Inventor 黄亦谦
Owner BEIJING QUALITY & ZEAL INFORMATION TECH CO LTD
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