Early Detection of Parkinson's Disease for Developing a Predictive Model Using Biomedical Voice Data

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Author(s): Muhammad Zubair (Ilma University, Pakistan)and Bushra Khalid (Sirsyed University, Pakistan)
Copyright: 2026
Pages: 30
Source title: Precision in CT Imaging for Personalized Implants and Surgical Planning
Source Author(s)/Editor(s): Soobia Saeed (Taylor's University, Malaysia)and Mohsin Qadeer (National Medical Center, Pakistan)
DOI: 10.4018/979-8-3373-2807-2.ch006

Keywords: Knowledge Management and Library Science / Medical Imaging / Medical Information Science Reference / Surgery and Surgical Specialties

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Abstract

The quality of life of every patient suffering from Parkinson's disease is significantly hindered by tremors, muscle rigidity, and other symptoms of general backed-up stages of the disorder. Early detection in some instances has improved treatment, leading to higher quality of living. This study aims to devise a predictive model utilizing biomedical voice data to allow for early diagnosis of Parkinson's disease. By studying voice signals and extracting crucial features from them, the model will seek to discover factors that can be traced to the disease. Findings from this study would aid in initiating early and necessary interventions towards furthering treatment and provide insights into the role of voice-based biomarkers for the diagnosis of other neurological diseases.

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Early Detection of Parkinson's Disease for Developing a Predictive Model Using Biomedical Voice Data

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