From Generative AI to Enhanced Dementia Care: The Path to Early Detection and Intervention

The global incidence of dementia is on the rise, with more than 9.9 million new cases annually, equivalent to a new diagnosis every 3.2 seconds. This trend is set to escalate due to the aging population worldwide. In this talk, I will discuss groundbreaking research in the application of generative artificial intelligence (AI) for the early detection of dementia through conversations with the elderly. Our work focuses on identifying language markers that serve as early indicators of dementia and developing predictive models based on these markers, providing a cost-effective and widely accessible solution for mass screening. We introduced an innovative reinforcement learning framework to create a dialogue agent specifically designed to interact efficiently with older adults to identify signs of early dementia. This agent learns to navigate conversations by generating a disease-specific lexical probability distribution, aiming to enhance diagnostic accuracy while reducing the number of conversation turns required. Furthermore, to enhance the precision of language markers, we have pioneered a cross-modality learning framework that aligns language markers with brain imaging through a contrastive loss technique and improves language-based predictions with auxiliary imaging variables generated from language. Finally, I will present our latest advancements in developing a large-language model-based conversational chatbot. This chatbot is designed for cognitively demanding interactions that are not only user-friendly but also hold the potential to act as a therapeutic tool for mitigating cognitive decline among the general population.

Zoom information will be sent to e-HAIL members.