Artificial Intelligence in Alzheimer’s Disease: A Survey on Machine Learning and Deep Learning Applications in Healthcare

Abstract

A major global health issue, Alzheimer's disease (AD) affects millions of people. Over the next four decades, it is expected to affect 106 million people. Unfortunately, there are no effective drugs available to treat AD at this time, even though the disease is on the rise. Educative details regarding the urgent need to diagnose AD and find a cure for it. This study provides a concise overview of the significant potential of artificial intelligence (AI), deep learning (DL), and machine learning (ML) in diagnosis and treatment of Alzheimer's disease (AD). Detecting and treating Alzheimer's disease (AD) at an early stage is extremely difficult because the neurological condition progresses over time. By integrating AI into healthcare systems, intricate medical data may be examined, resulting in improved diagnosis and personalized treatment plans. Presently, artificial intelligence (AI) is being used in several ways to help with Alzheimer's disease (AD), including neuroimaging, cognitive evaluations, and risk stratification. The discussion is an argument on the benefits of AI in multimodal data processing, early diagnosis, and biomarker identification. Moreover, we note that AI-powered decision support systems can make care optimal for people with AD. The results support the need to conduct further studies and innovation in AI to deal with the increased Alzheimer's burden.