AI Remotely Detects Parkinson's Disease During Sleep

Doctors could soon evaluate Parkinson's disease by having patients do one simple thing--sleep. A new study led by MIT researchers trains a neural network to analyze a person's breathing patterns while sleeping and determine whether the subject has Parkinson's. Recently published in Nature Medicine, the work could lead to earlier detection and treatment. "Our goal was to create a method for detecting and assessing Parkinson's disease in a reliable and convenient way. Inspired by the connections between Parkinson's and breathing signals, which are high-dimensional and complex, a natural choice was to use the power of machine learning to diagnose and track the progression," said lead author Yuzhe Yang, a PhD student at MIT's Computer Science & Artificial Intelligence Laboratory. While notoriously difficult to pinpoint, Parkinson's has become the fastest-growing neurological disease globally.