Alzheimer's disease (AD) is a prevalent neurodegenerative disease affecting cognitive functions and is particularly common among elderly people worldwide. It is considered incurable, and its symptoms progressively deteriorate over time. Early detection of AD is critical for developing new and effective treatment strategies. Dementia causes irreversible damage to brain neurons, leading to changes in brain structure that can be analyzed through multifractal frameworks. This study focuses on developing an efficient computing technique to pre-process and classify AD, especially in the early stages. The development of additional non-invasive and cost-effective tools for identifying individuals in the preclinical or early clinical stages of AD is necessary. These tools can aid in early detection and potentially more effective therapeutic and preventative strategies for AD. Large clinical trials are necessary to validate these tools before implementing them in clinical practice. This review will summarize and highlight the most promising screening tools, including neuropsychiatric, clinical, blood, and neurophysiological tests.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.