The Role of Artificial Intelligence in the Diagnosis of Alzheimer's Disease - A Comprehensive Review

• Published in: 2025 International Conference on Machine Learning and Autonomous Systems (ICMLAS) pp. 720 - 725
• Main Authors: Pimprale, Varsha S., Gadade, Haridas D.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 10.03.2025
• Subjects: Accuracy; Alzheimer; Alzheimer's disease; Artificial Intelligence; Diagnosis; Genetics; Machine learning; Machine learning algorithms; Natural language processing; Neuroimaging; Prediction; Prediction algorithms; Reviews
• DOI: 10.1109/ICMLAS64557.2025.10968129

The escalating ratio of Alzheimer's disease (AD) highlights the need for new diagnostic methods and poses significant obstacles to rapid detection and treatment. This rigorous analysis explores how artificial intelligence (AI) can improve AD diagnosis using advanced computational techniques. Artificial intelligence (AI) techniques - fuzzy logic, machine learning (ML) and natural language processing (NLP), show tremendous achievements in interpreting complex biomedical issues such as genetic profiles, clinical records, neuroimaging, etc. This study demonstrates how AI-based algorithms can improve diagnostic accuracy, predict disease progression, and enable the development of personalized treatment plans by identifying biomarkers and subtle patterns that are often missed by traditional methods. This study also covers the difficulties of using AI in clinical practice, such as the unevenness of data, ethical issues, and the requirements for interdisciplinary cooperation. This document emphasizes the revolutionary potential of AI, which combines the current development and new trends to open previous treatment and better results of patients.