School of Medicine

School of Medicine joins NIH initiative to expand use of AI in biomedical research

Washington University School of Medicine in St. Louis is joining the National Institutes of Health (NIH)’s Bridge2AI program, an estimated $130 million initiative intended to expand the use of artificial intelligence (AI) in biomedical and behavioral research. One of the first projects involves building a database of diverse human voices and harnessing the tools of AI and machine learning to train computers to identify diseases based on characteristics of the human voice. (Image: Getty Images)

Imagine if one day in the future, doctors could diagnose throat cancer, Alzheimer’s, depression or other diseases based on the sound of a patient’s voice. To help make that a reality, Washington University School of Medicine in St. Louis is joining the National Institutes of Health (NIH) Bridge2AI program, an estimated $130 million initiative intended to expand the use of artificial intelligence (AI) in biomedical and behavioral research.

One of the first projects involves building a database of diverse human voices and harnessing the tools of AI and machine learning to train computers to identify diseases based on characteristics of the human voice. This effort — called Voice as a Biomarker of Health — will bring together researchers from 12 institutions in North America, including Washington University, to build the database, which will be ethically sourced and also protect patient privacy.

“There is evidence that well-designed computer models can predict who has dementia or cancer, for example, based on voice recordings, which would then supplement additional methods of diagnosis,” said Philip R. O. Payne, the Janet and Bernard Becker Professor, chief data scientist and director of the Institute for Informatics. “We also will be leading new efforts in education and workforce development in the area of AI and its applications in biomedicine. As part of that, this project will help define a whole new way of producing these types of complex data sets and sharing them — in ethical ways that safeguard privacy — with a broad variety of scientists.”

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