Biomedical Question Answering

Biomedical question answering (BQA) focuses on developing systems that accurately and efficiently answer questions posed in natural language about biomedical topics, drawing on vast amounts of scientific literature and databases. Current research emphasizes improving the factuality and reliability of answers, particularly for long-form questions, often employing large language models (LLMs) like GPT-style architectures, knowledge graph integration, and techniques like retrieval augmented generation (RAG) to overcome limitations of LLMs in handling the long tail of biomedical knowledge. The development of robust and reliable BQA systems holds significant potential for improving healthcare, accelerating scientific discovery, and providing efficient access to complex biomedical information for both professionals and the public.