Soppari, Kavitha and Vupperpally, Bharath and Adloori, Harshini and Agolu, Kumar and kasula, Sujith (2025) AI-powered early detection of neurological disease: Parkinson's disease. International Journal of Science and Research Archive, 14 (1). pp. 278-282. ISSN 25828185
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Abstract
Parkinson's disease (PD), a neurological illness that gradually compromises motor abilities. Tremors, muscle rigidity, and bradykinesia (slowness of movement) are symptoms of PD. Effective therapy depends on a prompt and accurate diagnosis, yet traditional diagnostic methods can be laborious and subjective. The goal of this study is to create a machine learning-based model that uses clinical information, like vocal characteristics, to detect Parkinson's disease. Through the use of advanced machine learning algorithms and the extraction of important data patterns, the project hopes to develop a trustworthy diagnostic tool that will help physicians identify Parkinson's disease (PD) early on, facilitating quicker interventions and improved patient care.
Item Type: | Article |
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Uncontrolled Keywords: | Jitter; Shimmer; MDVP; CatBoost; Vocal Features; PCA |
Subjects: | Q Science > Q Science (General) Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry |
Depositing User: | Editor IJSRA |
Date Deposited: | 05 Jul 2025 16:02 |
Last Modified: | 05 Jul 2025 16:02 |
URI: | https://eprint.scholarsrepository.com/id/eprint/66 |