ALZHEIMER'S VS ARTIFICIAL INTELLIGENCE: BUILDING A MEMORABLE FUTURE

Abstract

Alzheimer's Disease (AD) is one of the leading causes of dementia in the world, characterized by the progressive loss of memory and cognitive functions. With the increase in life expectancy and population aging, the early and accurate diagnosis of AD has become a priority in health systems. In this context, Artificial Intelligence (AI) has shown a promising tool to improve the diagnosis and management of the disease, especially through the analysis of neuroimaging tests, such as magnetic resonance imaging. The objective of this study is to review the applications of AI in the diagnosis of AD, highlighting the advances, challenges, and ethical implications involved. The research was based on an integrative literature review, using databases such as PubMed, Scielo and Google Scholar, with publications between 2015 and 2024. Articles that deal with the use of machine learning algorithms for early detection of changes associated with AD were analyzed. The results show that AI is able to identify patterns in neuroimaging exams that may go unnoticed by traditional methods, contributing to faster and more accurate diagnoses. In addition, AI makes it possible to personalize treatments, adjusting guidelines according to the individual characteristics of patients. However, challenges related to data privacy, financial forecasting, and training of professionals still pose barriers to large-scale implementation. It is concluded that AI offers significant potential to transform the diagnosis and treatment of AD, promoting earlier and more effective interventions. However, it is necessary to ensure that its use respects ethical and legal principles, ensuring the safety and privacy of patients. Future studies should focus on developing public policies that ensure equitable access to AI technologies in the field of health, improve the quality of life of Alzheimer's patients, and reduce the social and economic impact of the disease.