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 ...

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 ...

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%.

Researchers use machine-learning approach to identify mitochondria interactions as a novel biomarker in Parkinson's disease.

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

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

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 ...

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

A Duke-led research team has identified a blood-based biomarker to diagnose Parkinson’s disease, which may lead to earlier disease detection.

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.