Research Horizons


How Artificial Intelligence Can Improve Clinical Trial Recruitment

Feeling harried when recruiting patients for clinical trials as they visit the hospital emergency department for care? This tool—the Automated Clinical Trial Eligibility Screener© (ACTES)—might improve your odds of success.

Compared to manually screening electronic health records (EHRs) to identify study candidates, this tool reduced patient screening time by 34 percent and improved patient enrollment by 11.1 percent. The system also improved the number of patients screened by 14.7 percent and those approached by 11.1 percent, according to details published online in JMIR Medical Informatics.

“By leveraging natural language processing and machine learning technologies, ACTES was able to quickly analyze different types of data and automatically determine patients’ suitability for clinical trials.”

—Yizhao Ni, PhD

The software was pilot-tested in 2015. The new study evaluated the tool in real time in a busy emergency department, where clinical research coordinators recruited patients for six pediatric clinical trials.

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Publication Information
Original title: A Real-Time Automated Patient Screening System for Clinical Trials Eligibility in an Emergency Department: Design and Evaluation
Published in: JMIR Medical Informatics
Publish date: July 25, 2019
Read the study

Research By

Yizhao Ni, PhD
Division of Biomedical Informatics
Yizhao Ni’s research interest lies in the development of machine learning, natural language processing (NLP) and information retrieval techniques to assist clinical decision makin