Biomedical Knowledge Graph Question Answering

Abstract

Automatic question answering in the biomedical domain is developing rapidly, driven by the growing need for quick access and up-to-date clinical evidence for the diagnosis and treatment of diseases. As healthcare professionals, researchers, and patients increasingly seek timely, precise, and explainable answers from vast structured data sources, traditional information retrieval (IR) methods—which rely on searching across large document collections—often fall short in terms of efficiency and accuracy. To address this, biomedical knowledge graphs (KGs) are emerging as a trustworthy and efficiently queryable structure for retrieving relevant information in the form of question answering (QA).