Researchers at Weill Cornell Medicine have used machine learning to define three subtypes of Parkinson’s disease based on the pace at which the disease progresses. In addition to having the potential to become an important diagnostic and prognostic tool, these subtypes are marked by distinct driver genes. If validated, these markers could also suggest ways the subtypes can be targeted with new and existing drugs.
Machine learning helps define new subtypes of Parkinson’s disease
