Mission and Vision
Voice as a biomarker of health is one of 4 data generation projects funded by the NIH’s Bridge2AI program.
Our group, The Bridge2AI-Voice Consortium aims to integrate the use of voice as biomarker of health in clinical care by generating a substantial multi-institutional, ethically sourced, and diverse voice database linked to multimodal health biomarkers to fuel voice AI research and build predictive models to assist in screening, diagnosis, and treatment of a broad range of diseases. Data collection will be made possible by software through a smartphone application linked to electronic health records (EHR) and other health biomarkers such as radiomics, and genomics, and supported by federated learning technology to protect data privacy.
Based on the existing literature and ongoing research in different fields of voice research, our group has identified 5 disease categories for which voice changes have been associated to specific diseases and around which we aim to center the data acquisition efforts
1. Vocal Pathologies (Laryngeal cancers, Vocal fold paralysis, Benign laryngeal lesions)
2. Neurological and Neurodegenerative Disorders (Alzheimer’s, Parkinson’s, Stroke, ALS)
3. Mood and Psychiatric Disorders (Depression, Schizophrenia, Bipolar Disorders)
4. Respiratory disorders (Pneumonia, COPD, Heart Failure, OSA)
5. Pediatric diseases (Autism, Speech Delay)
The Pillars of our work
Bridge2AI-Voice, also known as The Precision Public Health Voice Data Generating Project, is founded upon three pillars: people, ethics, and data. Our project aims to integrate the use of voice as biomarker of health in clinical care by generating a substantial multi-institutional, ethically sourced, and diverse voice database linked to multimodal health biomarkers to fuel voice AI research and build predictive models to assist in screening, diagnosis, and treatment of a broad range of diseases.
Our mission includes generating the infrastructure and networks of people needed to develop and implement standardized methods for voice data collection to fuel scientific discovery and ethical development of AI/ML models. Not only are we creating networks, but we are educating the community and training the next generation of researchers through development of resources, educational content and the Voice AI Summer School.
Our consortium is building insights, knowledge, and frameworks for the ethical use of voice in the development of AI/ML models. We are developing diverse networks of stakeholders to understand the implications of voice AI in healthcare and to inform the development of ethical guidelines which can be utilized across voice AI research.
Our project is developing the tools and standards for the generation of flagship datasets for voice AI research. We are collecting data across 5 cohorts of diseases to fuel scientific discovery of voice as a biomarker of disease with the use of artificial intelligence.
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