Using Deep Learning Model (VGG-16) to Detect Parkinson's Disease

Registration ID: IJNRD_198167

Published ID: IJNRD2305974

DOI: http://doi.one/10.1729/Journal.34585

Peerzada Zubair Ul Islam , Basharat Shafi Masoodi

Parkinsons Disease, MRI, VGG-16, Machine Learning, ML

The paper proposes a deep-learning model to detect Parkinson's Disease (PD) from patients' magnetic resonance images (MRIs). PD is a prevalent neurodegenerative disease that affects the movement and speech abilities of elderly people, and patients with PD are prone to frequent falls that can result in severe injuries. The model aims to accurately predict whether a patient has PD or not, which could improve the accuracy of PD diagnosis and aid in early intervention. Early intervention is critical for managing the disease and improving patient outcomes. With this approach, patients can be more aware of their condition and plan their lives accordingly.

Published Paper   E-Certificate

Peerzada Zubair Ul Islam & Basharat Shafi Masoodi (May-2023). Using Deep Learning Model (VGG-16) to Detect Parkinson's Disease. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(5), j445-j459. http://doi.one/10.1729/Journal.34585

Volume 8 Issue 5, May-2023

Pages : j445-j459

Paper Reg. ID: IJNRD_198167

Published Paper Id: IJNRD2305974

Downloads: 000122003

Research Area: Engineering

Country: Kupwara, Jammu and Kashmir, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2305974.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2305974

Crossref DOI: http://doi.one/10.1729/Journal.34585

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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