Large Language Model for Understanding and Monitoring Elderly Neurocognition

Dementia affects millions of people worldwide, and early diagnosis is essential for getting the right care and support. Doctors rely on collateral histories (accounts from family members or caregivers) to understand changes in a person's memory and thinking. However, these histories can be incomplete, unstructured, or difficult to obtain, making diagnosis more challenging. This study will test LUMEN (Large Language Model for Understanding and Monitoring Elderly Neurocognition), an AI-powered conversation tool designed to help caregivers describe their loved one's symptoms more effectively. By asking structured questions and guiding the conversation, LUMEN can create clear, well-organised reports for memory clinic doctors. This could make assessments quicker, more accurate, and less stressful for families. We will test LUMEN in real-world clinics by asking caregivers and doctors to use