Predicting Alzheimer's Disease Using Artificial Intelligence and Machine Learning: A Comprehensive Analysis.

This article discusses the potential of artificial intelligence (AI) and machine learning (ML) in predicting and diagnosing Alzheimer's disease (AD). The paper explores various methodologies, including analyzing neuroimaging, genetic data, electronic health records (EHR), and speech and language patterns associated with cognitive decline. It also highlights challenges in integrating these technologies into clinical practice, such as data privacy concerns and algorithmic bias. The paper proposes future research directions, emphasizing the importance of multi-modal data integration, cloud-based solutions, and ethical considerations. The goal is to improve early detection and management of AD, ultimately enhancing patient outcomes and reducing the societal burden of the disease. [Extracted from the article]