APPLICATION OF ARTIFICIAL INTELLIGENCE IN THE DETECTION OF ALZHEIMER'S VIA MAGNETIC RESONANCE: A SYSTEMATIC REVIEW
DOI:
https://doi.org/10.36557/2009-3578.2025v11n2p835-854Keywords:
Alzheimer’s Disease; Artificial Intelligence; Magnetic Resonance Imaging; Deep Learning; Diagnostic Imaging.Abstract
Objective: To evaluate the application of Artificial Intelligence (AI) in Alzheimer’s Disease (AD) detection via Magnetic Resonance Imaging (MRI) through a systematic literature review. Methods: Systematic review following PRISMA protocol, searching PubMed/MEDLINE, Scopus, and Web of Science databases, selecting Qualis A articles published between 2022-2025. Rigorous inclusion/exclusion criteria and methodological quality assessment using AMSTAR 2 were applied. Results: Five studies were included in qualitative synthesis and three in quantitative synthesis. Deep learning techniques, especially Convolutional Neural Networks (CNNs), demonstrated superior accuracy (89%) compared to traditional machine learning methods (76-86%) in AD vs. normal controls classification. Explainable AI (XAI) emerged as a promising approach for interpretability. Identified biomarkers include hippocampal atrophy, white matter hyperintensities, and functional connectivity changes. Conclusion: AI represents a promising tool for AD diagnosis via MRI but requires multicenter studies with robust external validation for effective clinical implementation.
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