Classification method of drug-disease relationship based on neural network

Abstract

The present invention relates to a drug-disease relationship classification method based on a neural network, which belongs to the technical field of biomedical text mining and data mining, and solvesthe problem of more accurate and effective classification of drug-induced relationship among drug-induced diseases for the drug-induced entities labeled in biomedical literature. The method comprisesS1 constructing a drug-induced relationship candidate case set; 2 performing text processing on that biomedical literature; 3 constructing the domain knowledge; 4 constructing an input vector; 5 constructing a text-level semantic information sub-network model; S6 adopting an attention mechanism to form the final representation of knowledge; S7 constructing a drug-disease relationship classification model; S8 predicting drug-disease relationships in the biomedical literature. The method can automatically identify the entity relationship of drug diseases between sentences and within sentences effectively, and overcomes the existing methods that most systems utilize a large number of feature engineering methods based on the traditional machine learning methods.

Description

technical field [0001] The invention relates to the technical fields of biomedical text mining and data mining, in particular to a neural network-based drug-disease relationship classification method. Background technique [0002] Massive unstructured biomedical literature contains rich, cutting-edge and potential biomedical knowledge, and is an important source of knowledge for practitioners in the field of biomedicine. It is very urgent to apply text mining technology to automatically and efficiently extract relevant knowledge from this knowledge repository. Drugs, diseases, and their relationships are among the most searched topics by PubMed users worldwide, reflecting their centrality in biomedical fields such as drug discovery and safety alerts, as well as in healthcare. Drugs and diseases have multiple relationships, such as the therapeutic relationship. In addition, drugs and diseases often have the following two relationships. One is the putative mechanism relatio...

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to provide a neural network-based drug-disease relationship classification method, combined with domain knowledge, to automatically learn the chapter-level features in medical texts, so as to solve the drug-disease relationship between the marked drug-disease entities in biomedical literature The problem of classifying relationships more accurately and effectively

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