Artificial intelligence in clinical trial participant recruitment and retention: A scoping review and meta-analysis.

Ziran Yin¹, Yun-Chung Liu², Jonathan Chong Kai Liew³, Rui Yang⁴, Stephanie Hendren², Elisa Ma², Zhaomei Geng⁵, Jiahan Wang⁶, Henry Foote², Christopher Lindsell⁷, Chuan Hong¹

¹Biostatistics and Bioinformatics, Duke University, NC, USA.

²Duke University, NC, USA.

³School of Chemistry, Chemical Engineering and Biotechnology, Nanyang Technological University, Singapore, Singapore.

⁴Department of Biomedical Informatics, National University of Singapore, Singapore, Singapore.

⁵Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, CA, USA.

⁶University of Wisconsin-Madison, WI, USA.

⁷Duke Clinical Research Institute, Duke University, NC, USA.

PubMed PMC DOI PDF

Abstract

Recruitment and retention challenges continue to hinder the success of clinical trials. Artificial intelligence (AI) has emerged as a promising means to optimize various clinical trial processes; however, its impact specifically on recruitment and retention has not been comprehensively evaluated. This scoping review utilized the Joanna Briggs Institute framework and adhered to PRISMA-ScR guideline…

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