Enhanced transfer learning technique for the diagnosis of Alzheimer’s disease through mri image analysis

This paper presents a comprehensive study on cognitive analysis techniques and the implementation of machine learning models to detect Alzheimer’s Disease (AD) at an early stage. With the increasing prevalence of AD globally, early detection has become crucial to managing the disease progression effectively. The proposed methodology leverages neuroimaging datasets and cognitive metrics with a refined preprocessing pipeline, enabling better model accuracy. Various existing systems are re- viewed, and a novel system design is proposed using a hybrid learning model. The results indicate substantial improvements in detection precision, demonstrating the potential of AI-driven approaches in the medical diagnostic domain. Introduction