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A Biomedical Question Answering System Based on SNOMED-CT

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Knowledge Science, Engineering and Management (KSEM 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11061))

Abstract

Biomedical question answering system is an important research topic in biomedical natural language processing. To make full use of the semantic knowledge in SNOMED-CT for clinical medical service, we developed a biomedical question answering system based on SNOMED-CT, which has the following characteristics: (a) this system takes the semantic network in SNOMED-CT as a knowledge base to answer the clinical questions posed by physicians in natural language form, (b) a multi-layer nested structure of question templates is designed to map a template into the different semantic relationships in SNOMED-CT, (c) a template description logic system is designed to define the question templates and tag template elements so as to accurately represent question semantics, and (d) a textual entailment algorithm with semantics is proposed to match the question templates in order to consider both the flexibility and accuracy of the system. The experimental results show that the overall performance of the system has reached a high level, which can give 85% of the correct answer and be used as a biomedical question answering system in a real environment.

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Acknowledgements

This work has been supported by the National Natural Science Foundation of China under the contract numbers 61462010 and 61363036, and Guangxi Collaborative Innovation Center of Multi-source Information Integration and Intelligent Processing.

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Authors and Affiliations

  1. Key Lab of Multi-Source Information Mining and Security, College of Computer Science and Information Engineering, Guangxi Normal University, Guilin, 541004, China

    Xinhua Zhu, Xuechen Yang & Hongchao Chen

Authors
  1. Xinhua Zhu
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  2. Xuechen Yang
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  3. Hongchao Chen
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Corresponding author

Correspondence to Hongchao Chen .

Editor information

Editors and Affiliations

  1. University of Bristol, Bristol, United Kingdom

    Weiru Liu

  2. Università di Trento, Povo, Italy

    Fausto Giunchiglia

  3. Jilin University, Changchun, China

    Bo Yang

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Zhu, X., Yang, X., Chen, H. (2018). A Biomedical Question Answering System Based on SNOMED-CT. In: Liu, W., Giunchiglia, F., Yang, B. (eds) Knowledge Science, Engineering and Management. KSEM 2018. Lecture Notes in Computer Science(), vol 11061. Springer, Cham. https://doi.org/10.1007/978-3-319-99365-2_2

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  • DOI: https://doi.org/10.1007/978-3-319-99365-2_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-99364-5

  • Online ISBN: 978-3-319-99365-2

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