Different Smart Diagnosis Processes of Alzheimer'S Brain Disease Using Ai Techniques

Abstract

As the world's population ages and the load on healthcare systems increases, it is critical to diagnose Alzheimer's Disease (AD) which is the one of threatening disease of the era. most accuracy.. Different features of the brain structure are evaluated by different diagnostic techniques, such as brain MRI and blood markers, to identify abnormalities associated with AD. Acetylcholine, which is essential to hippocampal formation and is depleted in AD, is a neurotransmitter that plays a major role in memory and cognition. Metabolites are identified using multi-omics analysis as promising prognostic markers for the progression of AD, with the potential use in early detection and biomarker development. AI software is a crucial component of clinical practice since it helps with early AD detection, therapy, and comprehension of metabolic abnormalities. To overcome the difficulties presented by AD in aging populations, the convergence of multi-omics analysis, biomarkers, and AI heralds a viable strategy for early AD identification and therapy. © 2025 selection and editorial matter, Nilanjan Dey, Bitan Misra, Sayan Chakraborty. All rights reserved.