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

被引：2

作者：

Shen, Ying ^{[1
]}

Colloc, Joel ^{[2
]}

Jacquet-Andrieu, Armelle ^{[3
]}

Guo, Ziyi ^{[1
]}

Liu, Yong ^{[4
]}

机构：

[1] Peking Univ, Shenzhen Grad Sch, Sch Elect & Comp Engn SECE, Shenzhen 518055, Peoples R China

[2] Univ Havre, CIRTAI, 25 Rue Philippe Lebon, F-76086 Le Havre, France

[3] Univ Paris Ouest, MoDyCo, UMR CNRS 7114, 200 Ave Republ, F-92000 Nanterre, France

[4] IER Business Dev Ctr, Shenzhen, Peoples R China

来源：

SMART COMPUTING AND COMMUNICATION, SMARTCOM 2017 | 2018年 / 10699卷

基金：

中国国家自然科学基金;

关键词：

Clinical decision support; Data mining; Ontology construction; Decision support system; Case-Based Reasoning; CLINICAL DECISION;

D O I：

10.1007/978-3-319-73830-7_28

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：278 / 288

页数：11

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