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2018 | OriginalPaper | Chapter

Constructing Ontology-Based Cancer Treatment Decision Support System with Case-Based Reasoning

Authors : Ying Shen, Joël Colloc, Armelle Jacquet-Andrieu, Ziyi Guo, Yong Liu

Published in: Smart Computing and Communication

Publisher: Springer International Publishing

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Abstract

Decision support is a probabilistic and quantitative method designed for modeling problems in situations with ambiguity. Computer technology can be employed to provide clinical decision support and treatment recommendations. The problem of natural language applications is that they lack formality and the interpretation is not consistent. Conversely, ontologies can capture the intended meaning and specify modeling primitives. Disease Ontology (DO) that pertains to cancer’s clinical stages and their corresponding information components is utilized to improve the reasoning ability of a decision support system (DSS). The proposed DSS uses Case-Based Reasoning (CBR) to consider disease manifestations and provides physicians with treatment solutions from similar previous cases for reference. The proposed DSS supports natural language processing (NLP) queries. The DSS obtained 84.63% accuracy in disease classification with the help of the ontology.

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Metadata
Title
Constructing Ontology-Based Cancer Treatment Decision Support System with Case-Based Reasoning
Authors
Ying Shen
Joël Colloc
Armelle Jacquet-Andrieu
Ziyi Guo
Yong Liu
Copyright Year
2018
Book
Smart Computing and Communication

Print ISBN: 978-3-319-73829-1

Electronic ISBN: 978-3-319-73830-7

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-73830-7_28

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