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Predicting Drugs Suspected of Causing Adverse Drug Reactions Using Graph Features and Attention Mechanisms.

Jinxiang YangZuhai HuLiyuan ZhangBin Peng
Published in: Pharmaceuticals (Basel, Switzerland) (2024)
This study applies deep learning methods to construct the SDAJM model for three purposes: (1) identifying drugs suspected to cause adverse drug events (ADEs), (2) predicting the ADRs of drugs, and (3) other drug discovery tasks. The results indicate that this method can offer new directions for research in the field of ADRs.
Keyphrases
  • adverse drug
  • drug discovery
  • drug induced
  • deep learning
  • electronic health record
  • working memory
  • emergency department
  • pulmonary embolism
  • convolutional neural network
  • artificial intelligence