PHEE : a dataset for pharmacovigilance event extraction from text

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Abstract

The primary goal of drug safety researchers and regulators is to promptly identify adverse drug reactions. Doing so may in turn prevent or reduce the harm to patients and ultimately improve public health. Evaluating and monitoring drug safety (i.e., pharmacovigilance) involves analyzing an ever growing collection of spontaneous reports from health professionals, physicians, and pharmacists, and information voluntarily submitted by patients. In this scenario, facilitating analysis of such reports via automation has the potential to rapidly identify safety signals. Unfortunately, public resources for developing natural language models for this task are scant. We present PHEE, a novel dataset for pharmacovigilance comprising over 5000 annotated events from medical case reports and biomedical literature, making it the largest such public dataset to date. We describe the hierarchical event schema designed to provide coarse and fine-grained information about patients' demographics, treatments and (side) effects. Along with the discussion of the dataset, we present a thorough experimental evaluation of current state-of-the-art approaches for biomedical event extraction, point out their limitations, and highlight open challenges to foster future research in this area.

Item Type: Conference Item (Paper)
Subjects: Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
R Medicine > RM Therapeutics. Pharmacology
Divisions: Faculty of Science, Engineering and Medicine > Science > Computer Science
Library of Congress Subject Headings (LCSH): Pharmacovigilance -- Data processing, Drugs -- Side effects -- Reporting, Drug monitoring -- Data processing, Natural language processing (Computer science), Data mining
Journal or Publication Title: Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
Publisher: Association for Computational Linguistics
Place of Publication: Abu Dhabi, United Arab Emirates
Official Date: December 2022
Dates:
Date
Event
December 2022
Published
22 December 2022
Accepted
Page Range: pp. 5571-5587
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access (Creative Commons open licence)
Date of first compliant deposit: 20 February 2023
Date of first compliant Open Access: 20 February 2023
RIOXX Funder/Project Grant:
Project/Grant ID
RIOXX Funder Name
Funder ID
EP/T017112/1
[EPSRC] Engineering and Physical Sciences Research Council
EP/V048597/1
[EPSRC] Engineering and Physical Sciences Research Council
EP/X019063/1
[EPSRC] Engineering and Physical Sciences Research Council
1750978
[NSF] National Science Foundation (US)
EP/V020579/1
UK Research and Innovation
Conference Paper Type: Paper
Title of Event: Conference on Empirical Methods in Natural Language Processing
Type of Event: Conference
Location of Event: Abu Dhabi, United Arab Emirates
Date(s) of Event: 7-11 Dec 2022
Related URLs:
URI: https://wrap.warwick.ac.uk/173731/

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