King's College London

Research portal

What Would it Take to get Biomedical QA Systems into Practice?

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

Gregory Kell, Iain J. Marshall, Byron C. Wallace, André Jaun

Original languageEnglish
Title of host publicationProceedings of the 3rd Workshop on Machine Reading for Question Answering, MRQA 2021
EditorsAdam Fisch, Alon Talmor, Danqi Chen, Eunsol Choi, Minjoon Seo, Patrick Lewis, Robin Jia, Sewon Min
PublisherAssociation for Computational Linguistics (ACL)
Pages28-41
Number of pages14
ISBN (Electronic)9781954085954
Published2021
Event3rd Workshop on Machine Reading for Question Answering, MRQA 2021 - Punta Cana, Dominican Republic
Duration: 10 Nov 2021 → …

Publication series

NameProceedings of the 3rd Workshop on Machine Reading for Question Answering, MRQA 2021

Conference

Conference3rd Workshop on Machine Reading for Question Answering, MRQA 2021
Country/TerritoryDominican Republic
CityPunta Cana
Period10/11/2021 → …

Bibliographical note

Funding Information: This work was supported in part by the National Institutes of Health (NIH), grant R01-LM012086. GK holds a doctoral studentship co-sponsored by Metadvice and the Guy's and St Thomas' Biomedical Research Centre. Funding Information: This work was supported in part by the National Institutes of Health (NIH), grant R01-LM012086. Publisher Copyright: © 2021 Association for Computational Linguistics.

King's Authors

Abstract

Medical question answering (QA) systems have the potential to answer clinicians' uncertainties about treatment and diagnosis on-demand, informed by the latest evidence. However, despite the significant progress in general QA made by the NLP community, medical QA systems are still not widely used in clinical environments. One likely reason for this is that clinicians may not readily trust QA system outputs, in part because transparency, trustworthiness, and provenance have not been key considerations in the design of such models. In this paper we discuss a set of criteria that, if met, we argue would likely increase the utility of biomedical QA systems, which may in turn lead to adoption of such systems in practice. We assess existing models, tasks, and datasets with respect to these criteria, highlighting shortcomings of previously proposed approaches and pointing toward what might be more usable QA systems.

View graph of relations

© 2020 King's College London | Strand | London WC2R 2LS | England | United Kingdom | Tel +44 (0)20 7836 5454