BioASQ is a series of international challenges promoting advances in biomedical semantic indexing and question answering. In this direction, it organizes different shared tasks annually, developing respective benchmark datasets that represent the real information needs of experts in the biomedical domain. The datasets for the question answering tasks (B and Synergy) include biomedical questions and answers in English annotated with relevant scientific papers and snippets, suited for the development and evaluation of question answering approaches. Manual scores are also available for each answer, indicating its quality and potentially the difficulty of the question. In this study, we analyze the benchmark datasets for biomedical Question Answering, investigate the particular challenges of answering biomedical questions with state-of-the-art question-answering approaches, such as Large Language Models, and explore machine-learning techniques to address them.
Relevant literature:
BioASQ-QA : A manually curated corpus for Biomedical Question Answering
Overview of BioASQ 2024: The Twelfth BioASQ Challenge on Large-Scale Biomedical Semantic Indexing and Question Answering