A Paraphrase Generation System for EHR Question Answering
Sarvesh Soni, Kirk E Roberts · 2019
This paper proposes a dataset and method for automatically generating paraphrases for clinical questions relating to patient-specific information in electronic health records (EHRs).Crowdsourcing is used to collect 10,578 unique questions across 946 semantically distinct paraphrase clusters.This corpus is then used with a deep learning-based question paraphrasing method utilizing variational autoencoder and LSTM encoder/decoder.The ultimate use of such a method is to improve the performance of automatic question answering methods for EHRs.