Machine learning can predict subtypes of Parkinson’s disease using images of patient-derived stem cells, an advance that could lead to personalised medicine and targeted drug discovery.

Using deep learning techniques, the team achieved 92.8 percent sensitivity and 86.2 percent specificity for Parkinson’s Disease detection. Not only is their proposed framework performing well, but it ...

Harnessing the strength of AI, researchers illuminate distinct Parkinson's disease types, successfully forecasting subtypes through patient stem cell imagery.

Scientists from UNSW Sydney with collaborators at Boston University have developed a tool that shows early promise in detecting Parkinson’s disease years before the first symptoms start appearing.

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%.

An effort to diversify genetic studies has led to a discovery about Parkinson's disease: a gene variant that raises the risk of Parkinson's in people of African ancestry.

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 ...