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Biomedical Question Answering: A Survey of Approaches and Challenges

Published:18 January 2022Publication History
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Abstract

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 five 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 we discuss some potential future directions to explore.

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  1. Biomedical Question Answering: A Survey of Approaches and Challenges

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          cover image ACM Computing Surveys
          ACM Computing Surveys  Volume 55, Issue 2
          February 2023
          803 pages
          ISSN:0360-0300
          EISSN:1557-7341
          DOI:10.1145/3505209
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          Publication History

          • Published: 18 January 2022
          • Accepted: 1 September 2021
          • Revised: 1 August 2021
          • Received: 1 March 2021
          Published in csur Volume 55, Issue 2

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