2025 News

We are pleased to announce the release of Bridge2AI-Voice v1.0, a dataset designed to advance research into the use of voice as a biomarker of health. This dataset, developed as part of the NIH Bridge2AI initiative, aims to support artificial intelligence research by providing ethically sourced, high-quality voice-derived data linked to clinical information.

Bridge2AI-Voice v1.0 includes 12,523 voice-derived recordings from 306 participants across five North American sites. Participants were selected based on conditions known to affect vocal characteristics, including:

• Voice disorders (e.g., laryngeal conditions affecting phonation)
• Neurological and neurodegenerative disorders (e.g., Parkinson’s, ALS, stroke)
• Mood and psychiatric disorders (e.g., depression, anxiety)
• Respiratory disorders (e.g., asthma, chronic cough)
• Pediatric voice and speech disorders

The initial release does not include raw voice recordings. Instead, it provides derived acoustic features, such as spectrograms, along with detailed demographic, clinical, and validated questionnaire data.

This year's Challenge focuses on detecting Chagas disease from ECGs. Chagas disease is a parasitic disease in Central and South America that affects an estimated 6.5 million people and causes nearly 10,000 deaths annually. Timely treatment may prevent or slow damage to the cardiovascular system, but serological testing capacity is limited, so detection through ECGs can help to identify potential Chagas patients for testing and treatment.