Machine learning reveals two main Parkinson's types and five subgroups

Machine learning reveals two main Parkinson's types and five subgroups

A new study led by researchers from VIB and KU Leuven shows that Parkinson's disease can be divided into distinct subtypes, helping explain why a single treatment does not work for all patients. Using a machine-learning-driven analysis, the team identified two main groups and five subgroups of the disease, marking an important step toward more personalized therapies. The findings are published in Nature Communications.

AI shows two main Parkinson's types and five subgroups

Researchers in Belgium have discovered that Parkinson’s disease may consist of several hidden subtypes rather than one single disorder. Using artificial intelligence and machine learning, scientists identified different biological forms of Parkinson’s disease that respond differently to treatments. The findings, published in Nature Communications, could eventually help doctors develop more personalized therapies for patients. Parkinson’s […] The…