AI-Assisted Anaerobic Threshold Interpretation in Cardiopulmonary Exercise Testing
This prospective randomized two-period crossover reader study will evaluate whether assistance from a frozen artificial intelligence model improves physicians' interpretation of the anaerobic threshold (AT) in cardiopulmonary exercise testing (CPET). Sixteen physicians, including 8 senior and 8 junior readers, will each interpret 150 de-identified CPET examinations once without AI assistance and once with AI assistance. The primary outcome is the within-physician difference in absolute AT localization error between the assisted and unassisted conditions. Secondary outcomes include signed timing error, agreement on whether AT is present, estimates within 15 and 30 seconds of the reference, inter-reader reliability, interpretation time, and whether the effect of AI assistance differs by physician seniority.
Age 18 years or older. [+5]
Direct involvement in development, training, hyperparameter selection, or checkp... [+3]