Dr. Moberly started working with Metin Gurcan, PhD, an expert in artificial intelligence (AI) at The Ohio State University, in 2015. Their teams collaborated on an AI system that converts various frames from an ear exam video into a still image with better lighting, focus, and digitally removed obstructions, with the help of a National Institutes of Health Award.
FREMONT, CA: Otologic Technologies, a Wisconsin-based health-tech startup developing an artificial intelligence (AI) system to improve treatment of ear disease, has declared the issuance of US Patent No. 10,932,662, "System and Method of Otoscopy Image Analysis to Diagnose Ear Pathology." The patent explains a new artificial intelligence system to help doctors better diagnose ear disease.
"One of the biggest challenges in diagnosing ear disease is the difficult nature of an ear exam," stated Aaron Moberly, MD, associate professor of otolaryngology at The Ohio State University and one of the inventors of the technology. "Even experienced doctors can have trouble with a live ear exam, as patients are usually uncomfortable and the view can be obstructed. Today's ear exam process doesn't scale well into the modern world of telemedicine and remote diagnosis."
Dr. Moberly started working with Metin Gurcan, PhD, an expert in artificial intelligence (AI) at The Ohio State University, in 2015. Their teams collaborated on an AI system that converts various frames from an ear exam video into a still image with better lighting, focus, and digitally removed obstructions, with the help of a National Institutes of Health Award. Their efforts resulted in the publication of nine academic papers as well as the filing of a US patent application on March 2, 2021. The patent application's international versions are currently being reviewed.
"Our approach is to apply artificial intelligence techniques to otoscopy and help primary care providers and advance care practitioners," stated Dr. Gurcan. Advanced care practitioners such as physician's assistants and nurse practitioners are increasingly dependent on for diagnosing ear disease in primary care offices and rural health clinics.
