Early Detection of Alzheimer's disease by using the Latest Techniques

Abstract

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.