Automatic Question Answering (QA) has been successfully applied in various
domains such as search engines and chatbots. Biomedical QA (BQA), as an
emerging QA task, enables innovative applications to effectively perceive,
access and understand complex biomedical knowledge. There have been tremendous
developments of BQA in the past two decades, which we classify into 5
distinctive approaches: classic, information retrieval, machine reading
comprehension, knowledge base and question entailment approaches. In this
survey, we introduce available datasets and representative methods of each BQA
approach in detail. Despite the developments, BQA systems are still immature
and rarely used in real-life settings. We identify and characterize several key
challenges in BQA that might lead to this issue, and discuss some potential
future directions to explore.

自动问答系统在不同领域有成功应用，生物医学问答是一项新兴任务。本文对生物医学问答的五种不同方法、可用数据集和代表性方法进行了详细介绍，并确定了该领域尚未成熟、面临的困境以及未来探索方向。