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Study identifier: NCT07463833 Synced from ClinicalTrials.gov · July 28, 2026
● Recruiting

Artificial Intelligence (AI)-Enhanced Pretreatment Peer-review Process to Improve Patient Safety in Radiation Oncology

Condition: Cancer · Prostate Cancer  ·  Sponsor: UNC Lineberger Comprehensive Cancer Center

PhaseNA
Planned participants207
Who can joinAll sexes, 18 Years to no upper limit
Healthy volunteersYes

About this study

This prospective study will test artificial intelligence (AI) and machine learning (ML) decision support tools. This tool is designed to help doctors, physicists and other staff during pre-treatment peer review, a step where treatment plans are checked before a patient begins care. The system highlights summaries showing how different providers may vary in their treatment planning (provider-variability summaries) and points out the best signals or warning signs to look for (optimal cues). By drawing attention to these patterns and cues, the tool aims to help reviewers spot possible treatment-planning mistakes earlier, reduce the chance of errors, and improve overall patient safety.

This description comes directly from the study's public registry record.

Talk to the study team

Olivia Morton  ·  (984) 974-8441  ·  olivia_roberts@med.unc.edu

Victoria Xu  ·  (984) 974-8444  ·  victoria_xu@med.unc.edu

Always discuss trial participation with your own doctor first.

Locations (1)

University of North Carolina at Chapel Hill, Department of Radiation OncologyChapel Hill, North Carolina, United StatesRecruiting

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Source record: clinicaltrials.gov/study/NCT07463833