Knowledge graph-based adverse drug reaction prediction system and method

Abstract

The invention relates to an adverse drug reaction prediction system and method based on a knowledge graph, the system comprises a database module, a knowledge graph module and a prediction module, the database module is connected with the knowledge graph module, and the knowledge graph module is in interactive connection with the prediction module. The database module is used for constructing a database containing a plurality of drug names and corresponding adverse reaction data; the knowledge graph module is used for inquiring the adverse reaction of the to-be-detected medicine from the database and drawing a corresponding knowledge graph; judging whether adverse reaction conflicts exist among the plurality of to-be-detected medicines or not, and drawing a corresponding knowledge graph; the prediction module is used for predicting the potential adverse reaction of the to-be-detected medicine. Compared with the prior art, the method has the advantages that the known adverse reaction of the to-be-detected medicine can be quickly and accurately inquired, the potential adverse reaction of the medicine can be predicted, and meanwhile, the adverse reaction conflict among multiple medicines can be judged, so that the harm possibly generated by multi-medicine combination is avoided.

Description

technical field [0001] The invention relates to the technical field of intelligent medical treatment, in particular to a knowledge graph-based adverse drug reaction prediction system and method thereof. Background technique [0002] Side effects of drugs (ADRs), also known as adverse drug reactions, are the possible, unexpected, and sometimes dangerous effects of drugs, and are one of the leading causes of morbidity and mortality in medical care. Adverse drug reactions mainly include allergic reactions, sequelae, heterogeneous reactions, dependence, dual infection, carcinogenicity, mutation and so on. In addition, anti-infective drugs also contain side effects due to drug quality problems and improper use. These side effects may occur when the drug itself contains impurities or is not used. [0003] To this end, it is necessary to predict the adverse reactions of drugs, so that users can know the adverse reactions of drugs in time, and assist doctors in the operation of dru...

AI Technical Summary

Problems solved by technology

Traditional research methods for the prediction of adverse drug reactions mostly use binary prediction, which can only predict the adverse reactions of a single drug. It is very likely that interactions or conflict reactions will occur, which will further increase the probability of adverse drug reactions and increase the difficulty of predicting adverse drug reactions; in addition, most of the existing technologies can only query and obtain currently known adverse reaction data, but cannot predict Potential unknown adverse reactions of drugs

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