Background Early diagnosis of Parkinson's disease (PD) is crucial for personalized
medicine and improved patient outcomes. Traditional methods often lack transparency …

Background Early diagnosis of Parkinson's disease (PD) is crucial for personalized
medicine and improved patient outcomes. Traditional methods often lack transparency …

Parkinson's disease (PD) is the second most common neurodegenerative disease affecting
millions of people all over the world. Accurate diagnosis is important to enable prompt …

Parkinson's disease (PD) is a prevalent neurodegenerative disorder known for its impact on
motor neurons, causing symptoms like tremors, stiffness, and gait difficulties. This study …

This chapter explores how using advanced optimization approaches might improve
Parkinson's disease (PD) prediction models. The main goal is to improve the predicting …

Objectives This study presents PD Predict, a machine learning system for Parkinson disease
classification using voice as a biomarker. Methods We first created an original set of …

Parkinson's Disease (PD) is a persistent neurological condition that has a global impact on a
significant number of individuals. The timely detection of PD is imperative for the efficacious …

Background and objectives Parkinson's Disease (PD) is a devastating chronic neurological
condition. Machine learning (ML) techniques have been used in the early prediction of PD …

A neurodegenerative disorder without permanent cure, Parkinson's Disease (PD)
increasingly hinders motor and cognitive abilities. Timely intervention of neuroprotective …

Parkinson's disease (PD) is a neurodegenerative disorder that affects millions of people
worldwide. The diagnosis of PD is based on clinical and neuroimaging data. This work …