Biomedical Concept

Biomedical concept extraction and linking aim to automatically identify and connect medical terms across diverse data sources like electronic health records and research literature, facilitating more efficient and insightful analysis of healthcare data. Current research focuses on leveraging large language models (LLMs) and graph neural networks, often incorporating techniques like prompt engineering, co-clustering, and contrastive learning to improve accuracy and address challenges posed by variations in terminology and data sparsity. These advancements are significantly impacting healthcare by enabling improved disease prediction, risk stratification, and the development of more robust and interpretable clinical decision support systems.