Population Graph

Population graphs represent patient cohorts as interconnected networks, leveraging graph neural networks (GNNs) to analyze relationships between individuals and predict outcomes like disease risk or brain age. Current research emphasizes developing robust methods for constructing these graphs from diverse multimodal data (imaging, clinical records), including exploring adaptive graph learning and pre-training techniques to improve model performance and address data scarcity. This approach holds significant promise for improving diagnostic accuracy, personalized medicine, and risk stratification in various medical domains, particularly where understanding patient-to-patient relationships is crucial.