Advancements in Artificial Intelligence-Based Alzheimer's Disease Classification Using Magnetic Resonance Imaging: A Comprehensive Review

Alzheimer's Disease (AD) presents substantial challenges in early diagnosis and classification, seeking innovative methods. This review study addresses various classification models developed for AD classification utilizing Magnetic Resonance Imaging (MRI) data and Artificial Intelligence (AI). This study reviews the benefits and drawbacks of several AI-driven strategies, from advanced deep learning architectures to conventional machine learning techniques, through a thorough analysis. These models provide promising pathways for accurate AD diagnosis by utilizing MRI data, allowing for early intervention and individualized treatment plans. Nonetheless, issues including the lack of data, the interpretability of algorithms, and validation in clinical contexts continue to exist. In order to fully utilize AI's potential to enhance patient care and AD classification, this review emphasizes the significance of interdisciplinary collaboration and strong validation procedures.