Machine learning applications in Alzheimer’s disease research: a comprehensive analysis of data sour

 Alzheimer’s disease is a debilitating neurological disorder that affects the central nervous system, causing significant disruption to cognitive processes. Predominantly afflicting the elderly, it leads to profound cognitive impairment. This study aims to review the application of machine learning techniques in the diagnosis and progression analysis of Alzheimer’s disease. A comprehensive review of 783 papers published from 2009 to 2023 was conducted, focusing on machine learning and deep learning techniques. Data sources included ADNI, OASIS, and localized patient data. The papers were categorized into 18 taxonomic classes and partitioned into five clusters based on neuroimaging and non-imaging methodologies. This categorization was underpinned by topic modeling and text mining methods, analyzing the semantic similarities in the papers. The study provides a detailed landscape of AI applications in Alzheimer’s research, highlighting the evolving role of machine learning in enhancing diagnostic accuracy and understanding disease progression.