Enhancing clinical name entity recognition based on hybrid deep learning scheme

Abstract

This paper describes a novel machine learning approach based on deeper and wider deep learning model, for better feature learning and latent feature discovery for the clinical name entity recognition task. The performance evaluation of the proposed framework with a benchmark clinical NLP dataset, the clinical CLEF eHealth challenge 2016 dataset, has led to promising performance, when assessed in terms of F-measure, Recall and Precision. The Hybrid CNN model with hyperparameter optimization led to an F-score 89 % for the CLEF eHealth 2016 Challenge task involving synthetic nursing handover dataset.