Machine Learning-Based Classification of Parkinson's Disease Patients Using Speech Biomarkers.

ABSTRACT:

Background

Parkinson's disease (PD) is the most prevalent neurodegenerative movement disorder and a growing health concern in demographically aging societies. The prevalence of PD among individuals over the age of 60 and 80 years has been reported to range between 1% and 4%. A timely diagnosis of PD is desirable, even though it poses challenges to medical systems.

Objective

This study aimed to classify PD and healthy controls based on the analysis of voice records at different frequencies using machine learning (ML) algorithms.

Methods

The voices of 252 individuals aged 33 to 87 years were recorded. Based on the voice record data, ML algorithms can distinguish PD patients and healthy controls. One binary decision variable was associated with 756 instances and 754 attr

SUBMITTER: Hossain MA 

PROVIDER: S-EPMC10836572 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature