Detecting Parkinson’s via breathing signals; plus Antisense, Noster and more

Massachusetts Institute of Technology scientists developed an artificial intelligence model to detect Parkinson’s disease and track its progression using breathing signals from radio waves that bounce off a person’s body during sleep. It detected Parkinson’s with an area-under-the-curve of 0.906 with a sensitivity of 86.23% and specificity of 82.83% using data from 7,671 individuals.

“We envision that the system could eventually be deployed in the homes of PD patients and individuals at high risk for PD (for example, those with LRRK2 gene mutation) to passively monitor their status and provide feedback to their provider,” said the authors of the Nature Medicine paper...