IBM's AI can predict how Parkinson's disease may progress in individuals

The model was trained on a dataset involving more than 1,400 patients.

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In the past, we’ve seen doctors use AI software to detect brain tumors, kidney illness and various cancers. Now, researchers from IBM and Michael J. Fox Foundation (MJFF) say they’ve developed a program that can predict how the symptoms of a Parkinson’s disease patient will progress in terms of both timing and severity. In The Lancet Digital Health journal, they claim the software could transform how doctors help patients manage their symptoms by allowing them to better predict how the disease will progress.

“Our aim is to use AI to help with patient management and clinical trial design. These goals are important because, despite Parkinson’s prevalence, patients experience a unique variety of motor and non-motor symptoms,” IBM said.

The breakthrough wouldn’t have been possible without the Parkinson’s Progression Markers Initiative, a study the Michael J. Fox Foundation sponsored. IBM describes the dataset, which includes information on more than 1,400 individuals, as the “largest and most robust volume of longitudinal Parkinson’s patient data to date” and says it allowed its AI model to map out complex symptom and progression patterns.

It’s estimated Parkinson’s disease affects more than 6 million people globally, and there’s currently no known cure for it. IBM Research and MJFF plan to continue work on the AI model. In the future, they hope to make it better at providing more granular characterizations of the various stages of the disease.

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