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Detection of Bleeding Events in Electronic Health Record Notes Using Convolutional Neural Network Models Enhanced With Recurrent Neural Network Autoencoders: Deep Learning Approach

Detection of Bleeding Events in Electronic Health Record Notes Using Convolutional Neural Network Models Enhanced With Recurrent Neural Network Autoencoders: Deep Learning Approach

Our HCLA model integrates a supervised CNN architecture and an unsupervised Bi LSTM-based autoencoder. Given a sentence as input, we trained a classifier to determine whether the sentence contains a bleeding event. Figure 1 illustrates the architecture of our model.

Rumeng Li, Baotian Hu, Feifan Liu, Weisong Liu, Francesca Cunningham, David D McManus, Hong Yu

JMIR Med Inform 2019;7(1):e10788

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