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October 2, 2025International Journal BioautomationOpen Access

Alzheimer’s Disease Dementia Detection Using Transfer Learning Based Convolutional Neural Network Model

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Authors

ADAmar A. DumKKKshama V. KulhalliPSPriyanka Singh

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Overview

The study demonstrates improved accuracy for Alzheimer's detection using transfer learning, suggesting better diagnostic tools. Evaluating models, it highlights the effectiveness of ResNet architectures.

Key Points

  • ResNet101 achieved the highest accuracy of 98.57% for detecting Alzheimer’s disease.
  • The study evaluated multiple models, with ResNet variants consistently outperforming GoogleNet at 96.32% accuracy.
  • Using MRI images from the ADNI database, the study provides insights into enhancing automated diagnostics for dementia.
  • Results suggest that transfer learning can significantly improve the precision of Alzheimer’s detection techniques.

Cite This Study

Dum et al. (2025) studied this question.

synapsesocial.com/papers/68de79595b556a9128e1a249https://doi.org/10.7546/ijba.2025.29.3.000950
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