Early Parkinson's Disease Detection Using Machine Learning Approach

Parkinson's disease (PD) is a progressive neurodegenerative disorder that affects movement and motor skills. Early diagnosis and treatment of Parkinson's disease are crucial for improving patient outcomes; however, traditional diagnostic methods are time-consuming and subject to observer b...

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Bibliographic Details
Published inAsian Journal of Research in Computer Science Vol. 16; no. 2; pp. 36 - 45
Main Authors Adekunle, Abiona Akeem, Joseph, Oyerinde Bolarinwa, Olalekan, Ajinaja Micheal
Format Journal Article
LanguageEnglish
Published 09.06.2023
Subjects
Computer Science
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ISSN2581-8260
2581-8260
DOI10.9734/ajrcos/2023/v16i2337

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Summary:Parkinson's disease (PD) is a progressive neurodegenerative disorder that affects movement and motor skills. Early diagnosis and treatment of Parkinson's disease are crucial for improving patient outcomes; however, traditional diagnostic methods are time-consuming and subject to observer bias. This study aims to use a machine learning model for the detection of Parkinson's disease. The model will be trained on a public repository dataset of biomedical voice measurements from individuals with and without Parkinson's disease and its performance will be evaluated in terms of accuracy and precision. The results of this study have the potential to revolutionize the diagnosis of Parkinson's disease by providing a fast, non-invasive, and reliable diagnostic tool. The study's results could also have implications for the development of similar diagnostic tools for other neurodegenerative disorders.
ISSN:2581-8260
2581-8260
DOI:10.9734/ajrcos/2023/v16i2337