DeepAD-Insight: A Benchmark Evaluation of Deep Learning Architectures for Multiclass Alzheimer’s Disease Classification and Staging from Brain MRI Data

Paper ID: 44

Abstract

This study investigates deep learning techniques for early Alzheimer's Disease diagnosis using MRI images. Using a Kaggle dataset with 6,400 images across four categories, models like CNN, EfficientNetB0, ResNet-18, and autoencoders were trained, aiming to improve diagnostic accuracy and speed for AD detection.

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