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Weekly Update
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March 15, 2025 |
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Recruiting patients for clinical trials is a costly and time-consuming process. Could AI help?
In a new JAMA+ AI Conversations, we talked with Mass General Brigham’s Alexander Blood about his LLM tool designed to assess patient eligibility more accurately and efficiently than manual screening.
Also this week:
- A JAMA Viewpoint laid out the genesis of Trustworthy and Responsible AI Network (TRAIN) and strategies for ensuring effective and safe use of AI throughout the US health care system.
- A JAMA research letter by Blood et al. found that AI-assisted patient screening improved the rate of eligibility determination and enrollment compared with manual screening in a heart failure trial.
- An invited commentary published in JAMA Network Open reflected on a study of an employer-sponsored digital health platform.
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Medical News & Perspectives
JAMA
Study Finds AI Can Quickly Prescreen Patients for Clinical Trials, Speeding Enrollment
Yulin Hswen, ScD, MPH; Nora Collins
INVITED COMMENTARY
JAMA Network Open
Employer-Sponsored Digital Health Platforms for Mental Wellness—A Good Investment
Molly Candon, PhD; Rebecca E. Stewart, PhD
RESEARCH LETTER
JAMA
Manual vs AI-Assisted Prescreening for Trial Eligibility Using Large Language Models—A Randomized Clinical Trial
Ozan Unlu, MD; Matthew Varugheese, MS; Jiyeon Shin, BS, ALM; et al
VIEWPOINT
JAMA
Launching the Trustworthy and Responsible AI Network (TRAIN): A Consortium to Facilitate Safe and Effective AI Adoption
Peter J. Embí, MD, MS; David C. Rhew, MD; Eric D. Peterson, MD, MPH; et al
AUDIO
 Prescreening for Clinical Trial Eligibility Using Large Language Models
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