research-article

A framework of a logic-based question-answering system for the medical domain (LOQAS-Med)

Authors:

Sofia J. Athenikos,

Ari D. BrooksAuthors Info & Claims

SAC '09: Proceedings of the 2009 ACM symposium on Applied Computing

Pages 847 - 851

https://doi.org/10.1145/1529282.1529462

Published: 08 March 2009 Publication History

Abstract

Question-answering systems that provide precise answers to questions, by combining techniques for information retrieval, information extraction, and natural language processing, are seen as the next-generation search engines. Due to the growth and real-world impact of biomedical information, the need for question-answering systems that can aid medical researchers and health care professionals in their information search is acutely felt. In order to provide users with accurate answers, such systems need to go beyond lexico-syntactic analysis to semantic analysis and processing of texts and knowledge resources. Moreover, question-answering systems equipped with reasoning capabilities can derive more adequate answers by using inference. Research on question answering in the medical and health care domain is still in its inception stage. While several recent approaches to medical question answering have explored use of semantic knowledge, few approaches have exploited the utility of logic formalisms and of inference mechanisms. In this paper, we present a framework for a logic-based question-answering system for the medical domain, which uses Description Logic as the formalism for knowledge representation and reasoning. As a first step toward building the proposed system, we present semantic analysis and classification of medical questions.

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Cited By

Pawar DPhansalkar SSharma ASahu GAng CLim W(2023)Survey on the Biomedical Text Summarization Techniques with an Emphasis on Databases, Techniques, Semantic Approaches, Classification Techniques, and Similarity MeasuresSustainability10.3390/su1505421615:5(4216)Online publication date: 26-Feb-2023
https://doi.org/10.3390/su15054216
Wang LZhang TTian JLin H(2023)An Semantic Similarity Matching Method for Chinese Medical Question TextHealth Information Processing10.1007/978-981-19-9865-2_6(82-94)Online publication date: 22-Feb-2023
https://doi.org/10.1007/978-981-19-9865-2_6
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https://doi.org/10.4018/978-1-5225-7501-6.ch004
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cover image ACM Conferences

SAC '09: Proceedings of the 2009 ACM symposium on Applied Computing

March 2009

2347 pages

ISBN:9781605581668

DOI:10.1145/1529282

Conference Chairs:
Sung Y. Shin
South Dakota State University, United States
,
Sascha Ossowski
University Rey Juan Carlos, Spain

Copyright © 2009 ACM.

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Published: 08 March 2009

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SAC09: The 2009 ACM Symposium on Applied Computing

March 8, 2009 - March 12, 2008

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Cited By

Pawar DPhansalkar SSharma ASahu GAng CLim W(2023)Survey on the Biomedical Text Summarization Techniques with an Emphasis on Databases, Techniques, Semantic Approaches, Classification Techniques, and Similarity MeasuresSustainability10.3390/su1505421615:5(4216)Online publication date: 26-Feb-2023
https://doi.org/10.3390/su15054216
Wang LZhang TTian JLin H(2023)An Semantic Similarity Matching Method for Chinese Medical Question TextHealth Information Processing10.1007/978-981-19-9865-2_6(82-94)Online publication date: 22-Feb-2023
https://doi.org/10.1007/978-981-19-9865-2_6
Bihl TYoung II WWeckman G(2019)Defining, Understanding, and Addressing Big DataWeb Services10.4018/978-1-5225-7501-6.ch004(39-74)Online publication date: 2019
https://doi.org/10.4018/978-1-5225-7501-6.ch004
Zhang YLu WOu WZhang GZhang XCheng JZhang W(2019)Chinese medical question answer selection via hybrid models based on CNN and GRUMultimedia Tools and Applications10.1007/s11042-019-7240-1Online publication date: 1-Mar-2019
https://doi.org/10.1007/s11042-019-7240-1
Bihl TYoung II WWeckman G(2016)Defining, Understanding, and Addressing Big DataInternational Journal of Business Analytics10.4018/IJBAN.20160401013:2(1-32)Online publication date: Apr-2016
https://doi.org/10.4018/IJBAN.2016040101
Savova GPestian JConnolly BMiller TNi YDexheimer J(2016)Natural Language Processing: Applications in Pediatric ResearchPediatric Biomedical Informatics10.1007/978-981-10-1104-7_12(231-250)Online publication date: 9-Oct-2016
https://doi.org/10.1007/978-981-10-1104-7_12
Morrissey JZhao R(2013)R/questProceedings of the 10th International Conference on Flexible Query Answering Systems - Volume 813210.1007/978-3-642-40769-7_7(79-90)Online publication date: 18-Sep-2013
https://dl.acm.org/doi/10.1007/978-3-642-40769-7_7
Patrick JLi M(2012)An ontology for clinical questions about the contents of patient notesJournal of Biomedical Informatics10.1016/j.jbi.2011.11.00845:2(292-306)Online publication date: Apr-2012
https://doi.org/10.1016/j.jbi.2011.11.008
Savova GDeleger LSolti IPestian JDexheimer J(2012)Natural Language Processing: Applications in Pediatric ResearchPediatric Biomedical Informatics10.1007/978-94-007-5149-1_10(173-192)Online publication date: 24-Sep-2012
https://doi.org/10.1007/978-94-007-5149-1_10
Wong WThangarajah JPadgham L(2012)Contextual question answering for the health domainJournal of the American Society for Information Science and Technology10.1002/asi.2273363:11(2313-2327)Online publication date: 30-Oct-2012
https://doi.org/10.1002/asi.22733

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