We’re looking at different aspects of their voice, such as changes in voice quality after drinking water, to determine whether that can help us distinguish who’s at risk for aspiration. —Anaïs Rameau, MD
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January 2023
At present, her (and others’) ability to create clinically useful AI tools is limited by the availability of high-quality diverse datasets. Although clinicians and healthcare systems have amassed tremendous amounts of data in recent years, including vocal data and images, most of it is not currently labeled, collated, or accessible. That’s why Dr. Rameau is working with Yael Bensoussan, MD, director of the University of South Florida’s Health Voice Center in Tampa, and others on a National Institutes of Health (NIH)-funded research project to collect voice data and develop an AI-ready bioacoustics dataset. The project is part of the NIH Bridge to AI program, a $100 million investment in the future of medicine (Acosta CM. Artificial intelligence could soon diagnose illness based on the sound of your voice. NPR Illinois. October 10, 2022).
Diagnosing Otitis Media, Vestibular Disorders, and More
Researchers in otology are exploring the use of AI to diagnose otitis media, diagnose and manage vestibular disorders, optimize hearing aid technology, and predict sensorineural hearing outcomes (Otolaryngol Head Neck Surg. 2020;163:1123–1133).
“Diagnostics for ear imagery is a hot area for artificial intelligence in otology,” Dr. Crowson said. “Here at Mass Eye and Ear, we’ve developed an integrated algorithm into a handheld device that clips onto a smartphone to assist in the diagnosis of pediatric ear infections. It takes pictures of the child’s eardrum, and then the algorithm provides a diagnosis.”
The algorithm developed by Dr. Crowson’s team has a mean prediction accuracy rate of 80.8%. In a validation survey, 39 clinicians analyzed a sample set of 32 endoscopic images and achieved an average diagnostic accuracy of 65.%. The AI model achieved an accuracy of 95.5% (Otolaryngol Head Neck Surg. [published online ahead of print August 16, 2022]. doi:10.1177/01945998221119156). The diagnostic accuracy of otolaryngology generalists and subspecialists was similar to the model (79.2% for generalists and 81.8% for subspecialists, compared to 80.8% mean prediction accuracy for the AI model); however, the AI tool achieved greater accuracy than pediatricians (60.1%) and family or internal medicine physicians (59.1%), which suggests that AI-augmented tools may be particularly useful in urgent care and general medicine clinics.
AI-enhanced tools may eventually reduce rates of misdiagnosis of otitis media, which could also decrease unnecessary antibiotic prescriptions and surgical procedures. AI tools that can be used with smartphones may make it possible to “deliver high quality diagnostic interpretation anywhere in the world,” Dr. Crowson said.