Their work, published today in Nature Machine Intelligence, has shown that computer models can accurately classify four subtypes of Parkinson's disease, with one reaching an accuracy of 95%.

Scientists explore the utility of machine learning methods in the field of neurodegenerative disease diagnosis, prognosis, and treatment effect prediction.

Parkinson’s disease (PD) is growing more rapidly than any other neurological disease, which makes its early detection so important. Researchers have developed a new machine-learning tool that ...

These are then analyzed using machine learning models to classify emotional responses, high and low valence and arousal, and differentiate patients with Parkinson's disease (PD) from healthy ...

The mystery of how Parkinson’s disease progresses could be cracked thanks to researchers at the Australian National University (ANU) and machine learning.

Predictors of Parkinson disease in a Medicare population—An application of machine learning in early disease detection. Presented at: ISPOR 2020; May 18-20, 2020; Abstract AI2. https://bit.ly ...

Machine learning (ML) and artificial intelligence (AI) can help experts speed up the diagnosis and develop new treatments for Parkinson’s Disease. “By transforming our understanding of the ...

Using a machine-learning model, researchers have differentiated three subtypes of Parkinson's disease, which may benefit from distinct forms of treatment.

She told UPI the development of a simple blood test for early detection of Parkinson's disease "can offer new opportunities for seeking disease-changing therapeutics, which is impossible today as ...

Young-Onset Parkinson's Disease (YOPD) is on the rise in India. Genetic research is crucial for early diagnosis, offering hope for better management and understanding of this growing health concern.