A national databank of de-identified voices, combined with artificial intelligence, could lead to diagnosing and treating cancer, depression, autism, Alzheimer’s disease and voice disorders.
Vanderbilt University Medical Center is partnering with 11 institutions on a $14 million NIH-funded project led by the University of South Florida and Weill Cornell Medicine that aims to establish voice as a biomarker used in clinical care.
Called Voice as a Biomarker of Health, the project is one of several recently funded by the NIH Common Fund’s Bridge2AI program, designed to use AI to tackle complex biomedical challenges.
The voice project will build an ethically sourced, de-identified database of diverse human voices.
Machine learning models will use the data to identify diseases from the human voice.
“The drive for this data generation project is the critical need for multi-institutional, multimodal, datasets that are accessible to researchers while still maintaining strict standards for patient privacy,” said Maria Powell, PhD, CCC-SLP, assistant professor of Otolaryngology-Head and Neck Surgery at VUMC.
“Our project in particular focuses on acoustic (or voice) data linked to respiratory data, pulmonary and neurological imaging, quality-of-life measures, and other health-related biomarkers that can help us analyze different types of diseases,” she said.
The research team identified five disease cohort categories where voice changes have been associated with specific diseases including:
- Voice disorders: (laryngeal cancers, vocal fold paralysis, benign laryngeal lesions).
- Neurological and neurodegenerative disorders (Alzheimer’s, Parkinson’s, stroke, ALS).
- Mood and psychiatric disorders (depression, schizophrenia, bipolar disorders).
- Respiratory disorders (pneumonia, COPD, heart failure).
- Pediatric voice and speech disorders (speech and language delays, autism).
Powell, who was named principal investigator for the project’s Plan for Enhancing Diverse Perspectives (PEDP), is leading this project with co-investigator Toufeeq Ahmed, PhD, MS, assistant professor of Biomedical Informatics at Vanderbilt University Medical Center, to promote diversity in team recruitment, patient representation and educational programs.
Ahmed brings expertise and leadership to this project from his efforts leading, as principal investigator, the AIM-AHEAD (Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity) program, created to enhance participation and representation of researchers and communities underrepresented in the development of AI/ML models and to address health disparities and inequities.
“It is critical for AI projects to consider inclusion, diversity and equity in participant recruitment, data collection practices, AI algorithm and model development, and researcher diversity to advance scientific innovation and biomedical research through the inclusion of all voices,” Ahmed said.