Shaping the Future of Hearing Diagnostics

There are too few certified audiologists for every hearing patient in need. 34 million children worldwide have deafness or hearing loss, of which 60% of cases could have been prevented with early detection. By 2050, there could be over 700 million people with disabling hearing loss. Neurality frees up valuable time for diagnosticians.

Neurality helps diagnosticians access medical data immediately, review medical history, identify patterns, and recommend interventions. Our AI algorithms can instantly classify normal ranges versus pathological cases, identifying trends in massive amounts of historical data for quality assurance and precise validation.

Neurality uses records and analyzed EM brain waves and uses neural networks to interpret, and compare hearing loss data to automatically classify results and advise diagnosticians on the most likely diagnosis—from the classification of norms or potential disease.

Emotional variance in patients and providers is a persistent challenge of accurate diagnostics, especially in ABR tests where data from click stimuli  can easily be misinterpreted. Neurality bypasses the behavioral variables from patient or practitioner for a more objective outcome.

Traditional ABR test results are interpreted manually, with about a 50% deviation in interpretation by audiologists with working with the same data. By closing the gap and getting consistent precision above 90%, Neurality validates diagnostic accuracy.