The Role of Artificial Intelligence in Early Diagnosis of Alzheimer’s Disease and Associated Vascular Dementia: A Systematic Review

Abstract

Abstract This systematic review explores the role of artificial intelligence (AI) in the early diagnosis of Alzheimer’s disease (AD) and related dementias. A total of 20 studies from recent years were analyzed, focusing on various AI techniques such as deep learning, neural networks, and feature engineering. The studies utilized datasets such as AD neuroimaging initiative and OASIS, showcasing AI’s potential in detecting early-stage Alzheimer’s with high accuracy. However, challenges such as variability in methodologies, limited generalizability, and lack of real-world validation were identified. Ethical concerns and the need for model interpretability were also highlighted. Despite these challenges, AI models demonstrate promising capabilities for improving early diagnosis, but further research is needed to standardize approaches and ensure clinical applicability. This review underscores the importance of integrating AI tools into healthcare settings to enhance early detection and treatment strategies for AD.

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