Deep Bidirectional Recurrent Neural Networks as End-To-End Models for Smoking Status Extraction from Clinical Notes in Spanish
Santiago Esteban, Manuel Rodríguez Tablado, Francisco E. Peper, Sergio Terrasa, Karin Silvana Kopitowski
This paper compares a deep bidirectional RNN end-to-end model with traditional classifiers for smoking status extraction from Spanish clinical notes, finding the RNN achieves high accuracy with significantly less development time.
bioRxiv · Aug 3, 2018 · PreprintBioinformatics