Automating Clinical Trial Matches Via Natural Language Processing of Synthetic Electronic Health Records and Clinical Trial Eligibility Criteria

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 syntheti...

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Published inAMIA Summits on Translational Science proceedings Vol. 2024; p. 125
Main Authors Murcia, Victor M, Aggarwal, Vinod, Pesaladinne, Nikhil, Thammineni, Ram, Do, Nhan, Alterovitz, Gil, Fricks, Rafael B
Format Journal Article
LanguageEnglish
Published United States 2024
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ISSN2153-4063
2153-4063

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Summary: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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ISSN:2153-4063
2153-4063