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.

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 ...

Identifying Parkinson’s Disease early is crucial for slowing the disease progression and a new tool developed by Khalifa University can now detect the disease using sensors on the average smartphone.

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 ...

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

There is no blood test to identify the risk of non-genetic Parkinson’s disease, but that may change if UNSW chemists’ new machine-learning tool is validated.

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.