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Alzheimer's disease poses an escalating global health challenge, necessitating accurate and timely diagnosis for effective intervention. This study presents a novel approach to Alzheimer's detection utilising advanced machine learning techniques applied to brain MRI scans. Leveraging Explainable Artificial Intelligence (XAI) methods, the developed model not only detects Alzheimer's disease but also offers transparent insights into the intricate patterns within the MRI data. In an era where Alzheimer's prevalence is rising, our methodology provides a valuable tool for clinicians and patients. By employing XAI, individuals can gain a comprehensive understanding of their MRI results, enabling them to seek second opinions and fostering a deeper comprehension of their condition. This research marks a significant step towards democratising medical diagnostics, empowering individuals with knowledge and promoting informed decision-making in Alzheimer's diagnosis and management.
Deshmukh et al. (Thu,) studied this question.