This research introduces a groundbreaking framework that uses large language models to automate the adjudication of cardiovascular events in clinical trials, traditionally a manual, time-consuming process performed by medical experts.

• Reduces adjudication time and resource requirements while maintaining clinical accuracy
• Minimizes inter-reviewer variability and potential bias in clinical assessments
• Demonstrates potential for LLMs to interpret complex medical data and assist in critical diagnostic processes
• Establishes a scalable approach that could accelerate clinical trial timelines

This innovation addresses a critical bottleneck in cardiovascular clinical trials, potentially accelerating drug development timelines while maintaining rigorous standards for event classification and patient safety monitoring.

Automating Adjudication of Cardiovascular Events Using Large Language Models