Abstract:
This review explores how Artificial Intelligence (AI) is changing the way we detect Alzheimer's disease early on. Alzheimer's, a complex neurodegenerative condition, is difficult to diagnose due to its intricate biology and diverse symptoms. By using AI echniques like machine learning and data analysis, this paper investigates how these technologies are improving the early identification of Alzheimer’s. The review carefully examines different AI-driven methods that combine various data sources, including brain scans (MRI, PET), genetic data, and cognitive tests. Using AI algorithms, researchers and doctors can spot subtle patterns and markers that might indicate the beginning of Alzheimer's long before noticeable symptoms appear. Furthermore, this paper discusses how AI-based tools could impact clinical practice by enhancing current diagnostic methods, offering personalized risk assessments, and allowing for timely interventions. It also addresses the ethical considerations and challenges related to using AI in Alzheimer's diagnosis. By consolidating current research findings, this review highlights how AI is reshaping early Alzheimer's detection, potentially leading to better disease management and intervention strategies.
