Artificial intelligence model detects Parkinson's disease via nocturnal breathing signals

An at-home, artificial intelligence-based system identified individuals with Parkinson's disease and predicted disease severity and progression using nocturnal breathing signals, according to a study in Nature Medicine. "A relationship between Parkinson's and breathing was noted as early as 1817, in the work of Dr. James Parkinson," Dina Katabi, PhD, principal investigator at the MIT Jameel Clinic, said in a related MIT press release. "This motivated us to consider the potential of detecting the disease from one's breathing without looking at movements. "Some medical studies have shown that respiratory symptoms manifest years before motor symptoms, meaning that breathing attributes could be promising for risk assessment prior to Parkinson's diagnosis." Katabi and colleagues evaluated the AI model using a dataset of 7,671 individuals from several sources, including the Mayo Clinic, Massachusetts General Hospital sleep lab and observational clinical trials.