It takes a lot of time — and money — to diagnose Alzheimer’s disease. After running lengthy in-person neuropsychological exams, clinicians have to transcribe, review, and analyze every response in detail. But researchers at Boston University have developed a new tool that could automate the process and eventually allow it to move online. Their machine learning-powered computational model can detect cognitive impairment from audio recordings of neuropsychological tests — no in-person appointment needed. Their findings were published in Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association.
