What question did this study set out to answer?

The aim is to develop a system for the early detection and classification of Alzheimer's disease using brain MRI data.

April 17, 2026Open Access

A CNN-Based Framework for Multi-Class Classification of Alzheimer's Disease Using Brain MRI

IAIyanuoluwa Best Akinrinlola AAAyobami Ajetunmobi

Key Points

The aim is to develop a system for the early detection and classification of Alzheimer's disease using brain MRI data.
Utilized a convolutional neural network (CNN) for image classification
Developed the framework using Python and deep learning libraries
Evaluated the system on benchmark datasets for performance assessment
Demonstrated effective classification of Alzheimer's disease from brain MRI scans
Achieved high accuracy rates in distinguishing between different stages of the disease

Abstract

This study presents a deep learning-based approach using Convolutional Neural Networks (CNNs) for the classification and early detection of Alzheimer’s disease from medical imaging data. The system aims to assist in early diagnosis by learning discriminative features from brain scans. The implementation is developed in Python using modern deep learning libraries and evaluated on benchmark datasets.

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