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Relation Classification for Bleeding Events From Electronic Health Records Using Deep Learning Systems: An Empirical Study

Relation Classification for Bleeding Events From Electronic Health Records Using Deep Learning Systems: An Empirical Study

Beyond traditional RNN and CNN models, Li and Yu [13] evaluated a capsule network and multilayer perceptron (MLP) for single domain and multidomain relation classification tasks on EHR data sets and found that although there was a slight improvement, the capsule network model was not superior to the MLP model. Christopoulou et al [14] developed intrasentence models based on bidirectional long short-term memory (bi-LSTM) and attention mechanism.

Avijit Mitra, Bhanu Pratap Singh Rawat, David D McManus, Hong Yu

JMIR Med Inform 2021;9(7):e27527

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