FRONTAL LOBE DEMENTIA: THE INTEGRATION OF AI TECHNOLOGY FOR THE DIAGNOSIS AND MANAGEMENT

Abstract

Frontotemporal dementia (FTD), a subtype of frontal lobe dementia, is a progressive neurodegenerative disease characterized by unusual symptoms and difficult diagnosis and treatment. This paper presents a review of ow artificial intelligence (AI) technologies can help transform the challenges outlined above. Latest advances in neuroimaging and machine learning algorithms have already demonstrated great improvements in early detection, differential diagnosis and personalized care planning for frontal lobe dementia. Key AI applications including multi-modal biomarker integration, hierarchical classification models, and computer aided diagnostic systems, all which increase accuracy and reduce diagnostic errors, are synthesized from current research. Additionally, the review emphasizes the use of AI to monitor in real time, and develop novel, patient centered treatment strategies. Challenges to the full realization of the clinical practise benefits of AI include data standardization, ethical concerns and regulatory hurdles. Overall, it presents clear direction for how to use AI technologies to improve outcomes for patients and caregivers, and fundamentally change dementia care.