Exploring the feasibility of using ABACAS® as an automated cough frequency screening tool in chronic cough clinical trials

This study evaluated whether ABACAS®, an AI-based cough detection algorithm, could rapidly identify chronic cough trial participants using automated cough counts. Screening VitaloJAK® recordings from 85 patients were analysed, with automated results compared against human-verified cough counts. ABACAS achieved 95.6% accuracy, demonstrating potential to support fast and reliable clinical trial eligibility decisions based on 24-hour cough frequency.