Natural language processing to identify adverse drug events
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Updated: Jun 28, 2026

A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions
Published on: May 27, 2021
Michael Gysbers1, Richard Reichley, Peter M Kilbridge
1BJC HealthCare, Center for Healthcare Quality & Effectiveness; Washington University School of Medicine, St. Louis, MO, USA.
Abstract:
We tested and adapted Cancer Text Information Extraction System (caTIES), a publicly available natural language processing tool (NLP), as a method for identifying terms suggestive of adverse drug events (ADEs). Although caTIES was intended to extract concepts from surgical pathology reports, we report that it can successfully be used to search for ADEs on a much broader range of documents.
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