A Study on Artificial Intelligence and its Role in Redefining Alzheimer’s Disease Diagnostics
Keywords:
AD (Alzheimer's Disease), CNN (Convolutional Neural Networks), MRI (Magnetic resonance imaging), PET (Positron Emission Tomography)Abstract
This study Examines the use of ‘Artificial intelligence (AI)’ in developing revolutionary diagnostic approaches for Alzheimer's Disease (AD). Given the rising incidence of AD and the critical need for early and accurate diagnosis, AI presents promising solutions through advanced data analysis and pattern recognition.[1] This research reviews recent advancements in AI methodologies, including Deep learning frameworks, Convolutional Neural Networks (CNN), and explainable AI (XAI), applied to multimodal medical imaging such as MRI and PET scans. The study examines various datasets, evaluation metrics, and future directions in AI-based diagnostics, emphasizing the potential for integrating volumetric analysis, hyperparameter optimization, and multi-class classification to enhance diagnostic precision. The findings indicate that AI has the capability to significantly improve early detection, classification, and progression prediction of AD, offering valuable insights for clinical applications and the development of new therapeutic strategies.[12]
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References
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