Optimized Neural Network Architectures for Early Detection of Alzheimer\'s disease Using MRI Images

Topic: Amyloid, tau and blood-test diagnosis

Alzheimer's disease is a neurodegenerative disorder affecting millions globally, with early detection being critical for effective management. This study investigates the application of optimized neural network architectures for the automated detection of Alzheimer's disease from MRI scans. We employ transfer learning with pre-trained models (MobileNetV2, DenseNet121, ResNet50) and apply model optimization techniques to create compact yet accurate diagnostic tools. Throu gh quantization, we achieve significant model size reduction (75-77%) while maintaining high classification accuracy. The optimized MobileNetV2 model achieves 86.25% accuracy at only 22.5% of its original size, while our ensemble approach reaches 91.56% accuracy. These findings demonstrate that optimized neural networks can enable accessible and efficient Alzheimer's disease detection on resource-constrained devices, potentially extending diagnostic capabilities to underserved healthcare settings. The optimized models offer a promising path toward developing practical AI-based screening tools that can complement traditional diagnostic methods while being deployable in diverse clinical environments.

Key findings

• Throu gh quantization, we achieve significant model size reduction (75-77%) while maintaining high classification accuracy.
• These findings demonstrate that optimized neural networks can enable accessible and efficient Alzheimer's disease detection on resource-constrained devices, potentially extending diagnostic capabilities to underserved healthcare settings.

Why it matters

Optimized neural networks detected Alzheimer's disease from MRI scans with 86.25% accuracy for a compact MobileNetV2 model and 91.56% for an ensemble, while reducing model size by 75-77%. This is a diagnostic screening tool study, not a treatment, cure, or prevention.

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Study details

• Effect size86.25%; 22.5%; 91.56%
• Evidence strengthLow

Read the original

• DOI: 10.22214/ijraset.2025.70154
• Original source →
• Free full text: International Journal for Research in Applied Science and Engineering Technology →

Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).

@article{shelke2025-8bb43974,
  author  = {Shelke, T. P.},
  title   = {{Optimized Neural Network Architectures for Early Detection of Alzheimer's disease Using MRI Images}},
  journal = {International Journal for Research in Applied Science and Engineering Technology},
  year    = {2025},
  doi     = {10.22214/ijraset.2025.70154},
  url     = {https://doi.org/10.22214/ijraset.2025.70154}
}

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