AI-Enhanced Review for Cancer Treatment Safety
What You Need to Know Before You Apply
What is the purpose of this trial?
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.
Who Is on the Research Team?
Lukasz Mazur, PhD
Principal Investigator
UNC Lineberger Comprehensive Cancer Center
Are You a Good Fit for This Trial?
Inclusion Criteria
Exclusion Criteria
Timeline for a Trial Participant
Screening
Participants are screened for eligibility to participate in the trial
Pre-treatment Peer Review
AI-enhanced peer review process to identify and correct potential errors in radiation therapy treatment plans before therapy begins
Radiation Therapy
Patients receive radiation therapy with treatment plans reviewed and potentially adjusted based on AI-enhanced peer review
Follow-up
Participants are monitored for safety and effectiveness after treatment
What Are the Treatments Tested in This Trial?
Interventions
- AI-Enhanced Pretreatment Peer-review Process
How Is the Trial Designed?
2
Treatment groups
Experimental Treatment
Active Control
Radiation oncology providers engaged in peer-review at participating clinics.
Prostate cancer patients who receive radiation therapy contribute de-identified safety outcomes.
Find a Clinic Near You
Who Is Running the Clinical Trial?
UNC Lineberger Comprehensive Cancer Center
Lead Sponsor
Agency for Healthcare Research and Quality (AHRQ)
Collaborator
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