Transfer Learning from Pre‐trained 3D Models for Enhanced Parkinson's Disease Detection

Our transfer learning approach demonstrated excellent performance in PD detection, achieving 94.03% accuracy and 100% sensitivity. The significant improvement over the baseline model (75% accuracy) supports the effectiveness of utilizing pre-trained weights from diverse medical imaging tasks. These results establish a promising framework for developing reliable computer-aided diagnosis systems of PD and neurodegenerative diseases using MRI data.

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Publication Details

Journal
Alzheimer s & Dementia
Published
2025-12-01
DOI
https://doi.org/10.1002/alz70856_101856
Primary Topic
Parkinson's Disease Mechanisms and Treatments
Type
article
Field-Weighted Citation Impact
0.00
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Transfer Learning from Pre‐trained 3D Models for Enhanced Parkinson's Disease Detection

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Transfer Learning from Pre‐trained 3D Models for Enhanced Parkinson's Disease Detection

K. -M. Ng, Tanvi Verma, Lok Yee Tweety Au, Simon Kang Seng Ting, Adeline Su Lyn Ng, Shahul Hameed, Eng King Tan, Fei Gao, Siow Mong Rick Goh, Yong Liu, Mingrui Tan, Louis CS Tan, Jia Huang, Yuting Song
article en

Abstract

Our transfer learning approach demonstrated excellent performance in PD detection, achieving 94.03% accuracy and 100% sensitivity. The significant improvement over the baseline model (75% accuracy) supports the effectiveness of utilizing pre-trained weights from diverse medical imaging tasks. These results establish a promising framework for developing reliable computer-aided diagnosis systems of PD and neurodegenerative diseases using MRI data.

Alzheimer s & DementiaVol. 21(S2)
Agency for Science, Technology and Research (SG), Institute of High Performance Computing (SG), National Neuroscience Institute (SG)
Openalex Percentile: Top 31%
Parkinson's Disease Mechanisms and Treatments
DOIOpen Access PDFOpenAlex
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