Holistic Approaches to Monitoring Dementia Progression Beyond Cognitive Measures

This research aims to advance the diagnosis and management of vascular dementia by integrating machine learning and natural language processing into traditional diagnostic frameworks. The enhanced system targets the early detection of vascular dementia, a condition often overlooked by current neuropsychological tests. Unlike conventional methods, this proposed system provides continuous monitoring and real-time data analysis, enabling dynamic disease management. This approach not only increases diagnostic accuracy but also allows for timely interventions that could significantly alter disease progression and improve patient outcomes. Additionally, the system’s capability for personalized care helps tailor treatment plans to individual patient needs, optimizing therapeutic efficacy. The research also explores the potential for reducing healthcare costs through early diagnosis and efficient resource management. Overall, this study contributes to the field by offering innovative solutions that could revolutionize dementia research and treatment, potentially leading to broader applications for various cognitive disorders.