Improvements in screening precision with AI-enhanced clinical trial matching using EMR source data for cancer clinical trials.

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AI-native clinical trial matching improved precision compared to a rule-based approach, increasing eligibility screening.
The AI-native method identified fewer patients but resulted in a higher proportion of eligible candidates post-review.
Evaluation occurred across four cancer trials at an oncology practice, highlighting advantages in patient matching efficiency.
Continued efforts are needed to address limitations regarding eligibility determination and false negative rates in screening.

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Algorithmic methods help identify eligible patients for cancer trials, suggesting AI may enhance trial enrollment efficiency.

Petranovich et al. (2025) studied this question.

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