Entity-Enriched Neural Models for Clinical Question Answering

WS 2020 Bhanu Pratap Singh RawatWei-Hung WengPreethi RaghavanPeter Szolovits

We explore state-of-the-art neural models for question answering on electronic medical records and improve their ability to generalize better on previously unseen (paraphrased) questions at test time. We enable this by learning to predict logical forms as an auxiliary task along with the main task of answer span detection... (read more)

PDF Abstract WS 2020 PDF WS 2020 Abstract

Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper