Leveraging Artificial Intelligence for Clinical Study Matching: Key Threads for Interweaving Data Science and Implementation Science.

Andrew James Goodwin¹, Sara Ann Armstrong², David Ptak³, Kenneth Catchpole⁴, Jihad S Obeid⁵, Paul M Heider⁵

¹Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Medical University of South Carolina, Suite 816 CSB, MSC 630, 96 Jonathan Lucas St., Charleston, SC, 29425, United States, 1 8437924728.

²Department of Medicine, Medical University of South Carolina, Charleston, SC, United States.

³Biomedical Informatics Center, Medical University of South Carolina, Charleston, SC, United States.

⁴Department of Anesthesia and Perioperative Medicine, Medical University of South Carolina, Charleston, SC, United States.

⁵Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, United States.

PubMed PMC DOI PDF

Abstract

Artificial intelligence holds the potential to enhance the efficiency of clinical research. Yet, like all innovations, its impact is dependent upon target user uptake and adoption. As efforts to leverage artificial intelligence for clinical trial screening become more widespread, it is imperative that implementation science principles be incorporated in both the design and roll-out of user-facing…

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