Machine Learning Identifies Three Subtypes of Parkinson's Disease

Researchers at Weill Cornell Medicine have utilized machine learning to identify three subtypes of Parkinson's disease based on the speed at which the disease progresses. These subtypes are distinguished by distinct genetic drivers and have the potential to improve diagnosis and treatment strategies.
The study also revealed that the diabetes drug metformin may enhance symptoms, particularly in the rapidly progressing subtype. The findings pave the way for personalized treatment approaches for Parkinson's patients.
Brief news summary
Researchers at Weill Cornell Medicine have used machine learning to identify three subtypes of Parkinson's disease based on the pace at which the disease progresses. These subtypes, classified as Inching Pace, Moderate Pace, and Rapid Pace, have distinct genetic and molecular markers. The study also found that the diabetes drug metformin might improve symptoms, particularly in the rapidly progressing subtype. The findings could lead to personalized treatment approaches for Parkinson's patients. The researchers used deep learning to analyze deidentified clinical records and genetic profiles from two large databases and validated their findings using patient health records.
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