The pipeline illustrates how EEG signals are processed for Parkinson's disease detection. Key features are extracted from brainwave data and transformed into images or movie representations. These are ...

In a groundbreaking development for neurological care, scientists have unveiled an artificial intelligence-powered blood test that has the potential to detect Parkinson’s disease years before symptoms ...

Sensor data from wearable devices analyzed over five years reveals walking and posture differences that predict fall risk in Parkinson’s patients. Study: Predicting future fallers in Parkinson’s ...

Researchers have identify a set of biomarkers that could someday make it easy to spot the disease in a patient's blood sample. Parkinson's disease is best known for its effects on the central nervous ...

In a major step forward for Parkinson’s care, researchers have used machine learning and UK Biobank data to predict who is most at risk of developing Parkinson’s disease dementia (PDD), highlighting ...

A machine learning model differentiated Parkinson's disease, multiple system atrophy, and progressive supranuclear palsy. AUROCs and predictive values for distinguishing Parkinson's from mimics were ...

A longstanding mystery in Parkinson's disease research has been why some individuals carrying pathogenic variants that increase their risk of PD go on to develop the disease, while others who also ...

Parkinson's disease is often seen as a condition that primarily affects older adults. In reality, it can impact people at any age, with 10-20% of cases appearing before the age of 50, and about half ...

Investigators have developed a novel approach that can better identify and characterize genetic variant interactions associated with increased risk of Parkinson's disease, improving the understanding ...

Study: Microbiome and metabolome integrated analysis: exploring potential diagnostic approaches for Parkinson’s disease using tongue coating samples. Image credit ...