International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

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Xception model for efficient Parkinson's disease detection and prediction

Author(s) Ms. A Moni Sree
Country India
Abstract Parkinson’s disease affects movement due to loss of dopamine-producing brain cells. This project used deep learning with the Xception model on Kaggle clinical data to detect the disease early. After selecting key features, the model achieved 100% training and 97% test accuracy, showing strong potential for early diagnosis and treatment planning.
Keywords Parkinson's disease, dopamine, xception, kaggle
Field Computer Applications
Published In Volume 7, Issue 2, March-April 2025
Published On 2025-04-08
DOI https://doi.org/10.36948/ijfmr.2025.v07i02.41069
Short DOI https://doi.org/g9fb8p
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E-ISSN 2582-2160
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