Extraction-of-Adverse-Drug-Reaction-from-Unstructured-Data-using-Bidirectional-LSTM-Network
PublicFor this problem, we proposed the use of bidirectional-LSTM’s(Long Short Term Memory) with 1-D CNN layer to classify patient notes at character level and at word level. The 1-D CNN is employed to scale back the training time. In order to improve the performance, we will also feed the network combined word embedding consisting of Pre-trained word2vec 100 dimension word embedding trained on the Twitter ADR Dataset database and character embedding generated by a Char-CNN for Named Entity Recognition
adverse-drug-reactionbidirectional-lstmcnn-text-classificationdeep-learningdeep-neural-networksdrug-target-interactionsextractionlstmlstm-modellstm-neural-networks
Creat：2020-07-03T23:05:51
Update：2024-04-05T15:27:56
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