Browsing Health: Information Extraction to Support New Interfaces for Accessing Medical Evidence

Soham Parikh, Elizabeth Conrad, Oshin Agarwal, Iain Marshall, Byron Wallace, Ani Nenkova

Abstract
Standard paradigms for search do not work well in the medical context. Typical information needs, such as retrieving a full list of medical interventions for a given condition, or finding the reported efficacy of a particular treatment with respect to a specific outcome of interest cannot be straightforwardly posed in typical text-box search. Instead, we propose faceted-search in which a user specifies a condition and then can browse treatments and outcomes that have been evaluated. Choosing from these, they can access randomized control trials (RCTs) describing individual studies. Realizing such a view of the medical evidence requires information extraction techniques to identify the population, interventions, and outcome measures in an RCT. Patients, health practitioners, and biomedical librarians all stand to benefit from such innovation in search of medical evidence. We present an initial prototype of such an interface applied to pre-registered clinical studies. We also discuss pilot studies into the applicability of information extraction methods to allow for similar access to all published trial results.
Anthology ID:
W19-2606
Volume:
Proceedings of the Workshop on Extracting Structured Knowledge from Scientific Publications
Month:
June
Year:
2019
Address:
Minneapolis, Minnesota
Editors:
Vivi Nastase, Benjamin Roth, Laura Dietz, Andrew McCallum
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
43–47
Language:
URL:
https://aclanthology.org/W19-2606
DOI:
10.18653/v1/W19-2606
Bibkey:
Cite (ACL):
Soham Parikh, Elizabeth Conrad, Oshin Agarwal, Iain Marshall, Byron Wallace, and Ani Nenkova. 2019. Browsing Health: Information Extraction to Support New Interfaces for Accessing Medical Evidence. In Proceedings of the Workshop on Extracting Structured Knowledge from Scientific Publications, pages 43–47, Minneapolis, Minnesota. Association for Computational Linguistics.
Cite (Informal):
Browsing Health: Information Extraction to Support New Interfaces for Accessing Medical Evidence (Parikh et al., NAACL 2019)
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https://preview.aclanthology.org/add_acl24_videos/W19-2606.pdf
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