BioASQ at CLEF2021: Large-Scale Biomedical Semantic Indexing and Question Answering

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Abstract

This paper describes the ninth edition of the BioASQ Challenge, which will run as an evaluation Lab in the context of CLEF2021. The aim of BioASQ is the promotion of systems and methods for highly precise biomedical information access. This is done through the organization of a series of challenges (shared tasks) on large-scale biomedical semantic indexing and question answering, where different teams develop systems that compete on the same demanding benchmark datasets that represent the real information needs of biomedical experts. In order to facilitate this information finding process, the BioASQ challenge introduced two complementary tasks: (a) the automated indexing of large volumes of unlabelled data, primarily scientific articles, with biomedical concepts, (b) the processing of biomedical questions and the generation of comprehensible answers. Rewarding the most competitive systems that outperform the state of the art, BioASQ manages to push the research frontier towards ensuring that the biomedical experts will have direct access to valuable knowledge.

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APA

Krithara, A., Nentidis, A., Paliouras, G., Krallinger, M., & Miranda, A. (2021). BioASQ at CLEF2021: Large-Scale Biomedical Semantic Indexing and Question Answering. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12657 LNCS, pp. 624–630). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-72240-1_73

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