Objective This study evaluates the efficacy of voice analysis combined with machine
learning (ML) techniques in enabling the diagnosis of Parkinson's disease (PD). Methods …

Background: Early diagnosis is pivotal for the effective management of Parkinson's Disease
(PD). Voice analysis emerges as a promising non-invasive method for early detection of PD …

As voice technology continues to advance, clinical analysis of acoustic measures in speech
patterns has the potential for early detection of Parkinson's disease (PD), the second most …

Parkinson's disease (PD) is a chronic and progressive long-term degenerative disorder of
the central nervous system. The symptoms usually develop slowly, starting with symptoms in …

Materials and Methods We utilized a dataset of 195 voice samples with 23 attributes,
applying machine learning algorithms such as Linear Discriminant Analysis (LDA), Support …

Parkinson's Disease (PD) is a prevalent neurological condition characterized by motor and
cognitive impairments, typically manifesting around the age of 50 and presenting symptoms …

Abstract Background and Objective: Parkinson's disease is the second-most-common
neurodegenerative disorder that affects motor skills, cognitive processes, mood, and …

Numerous studies have reported on the high accuracy of using voice tasks for the remote
detection and monitoring of Parkinson's Disease (PD). Most of these studies, however …

The preliminary diagnosis and evaluation of the presence and/or severity of Parkinson's
disease is crucial in controlling the progress of the disease. Real-time, non-invasive …

Parkinson's Disease (PD) is one of the most common non-curable neurodegenerative
diseases. Diagnosis is achieved clinically on the basis of different symptoms with …