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Published on: September 20, 2018
Automating Clinical Trial Matches Via Natural Language Processing of Synthetic Electronic Health Records and Clinical
Victor M Murcia1,2, Vinod Aggarwal3,4, Nikhil Pesaladinne5
1VA Massachusetts Veterans Epidemiology Research and Information Center, Boston, MA.
Abstract:
Clinical trials are critical to many medical advances; however, recruiting patients remains a persistent obstacle. Automated clinical trial matching could expedite recruitment across all trial phases. We detail our initial efforts towards automating the matching process by linking realistic synthetic electronic health records to clinical trial eligibility criteria using natural language processing methods. We also demonstrate how the Sørensen-Dice Index can be adapted to quantify match quality between a patient and a clinical trial.
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