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

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, the second most prevalent neurodegenerative disorder among
individuals over the age of 65, poses challenges in early-stage detection, often requiring …

As the voice disorder is a typical early symptom of Parkinson, some researchers attempt to
diagnose this disease based on voice data collected from suspected patients. Although …

Voice technology has grown tremendously in recent years and using voice as a biomarker
has also been gaining evidence. We demonstrate the potential of voice in serving as a deep …

Abstract Machine learning approaches have been used for the automatic detection of
Parkinson's disease with voice recordings being the most used data type due to the simple …

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 …

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 …

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 Traditional classifier for the classification of diseases, such as K-Nearest
Neighbors (KNN), Linear Discriminant Analysis (LDA), Random Forest (RF), Logistic …