An Ontological Case Base Engineering Methodology for Diabetes Management

Ontology engineering covers issues related to ontology development and use. In Case Based Reasoning (CBR) system, ontology plays two main roles; the first as case base and the second as domain ontology. However, the ontology engineering literature does not provide adequate guidance on how to build, evaluate, and maintain ontologies. This paper proposes an ontology engineering methodology to generate case bases in the medical domain. It mainly focuses on the research of case representation in the form of ontology to support the case semantic retrieval and enhance all knowledge intensive CBR processes. A case study on diabetes diagnosis case base will be provided to evaluate the proposed methodology.

[1]  Jerry R. Hobbs,et al.  Time in OWL-S , 2004 .

[2]  Susan Craw,et al.  Integrating case-based reasoning with an electronic patient record system , 2011, Artif. Intell. Medicine.

[3]  Pornpit Wongthongtham,et al.  Development of patient-practitioner assistive communications (PPAC) ontology for type 2 diabetes management , 2012 .

[4]  L. Stokowski,et al.  NATIONAL GUIDELINE CLEARINGHOUSE , 2005 .

[5]  Peter Spyns Object Role Modelling for Ontology Engineering in the DOGMA Framework , 2005, OTM Workshops.

[6]  Claudia Horning Handbook of Metadata, Semantics and Ontologies , 2016 .

[7]  Pari Delir Haghighi,et al.  Development and evaluation of ontology for intelligent decision support in medical emergency management for mass gatherings , 2013, Decis. Support Syst..

[8]  Richard Gil,et al.  SMOL: a systemic methodology for ontology learning from heterogeneous sources , 2014, Journal of Intelligent Information Systems.

[9]  Euripides G. M. Petrakis,et al.  SOWL: A Framework for Handling Spatio-temporal Information in OWL 2.0 , 2011, RuleML Europe.

[10]  Miguel-Angel Sicilia,et al.  Handbook of Metadata, Semantics and Ontologies , 2013 .

[11]  Martin J. O'Connor,et al.  A Method for Representing and Querying Temporal Information in OWL , 2010, BIOSTEC.

[12]  Steffen Staab,et al.  On-To-Knowledge Methodology (OTKM) , 2004, Handbook on Ontologies.

[13]  Ibrahim F. Moawad,et al.  A New Hybrid Case-Based Reasoning Approach for Medical Diagnosis Systems , 2014, Journal of Medical Systems.

[14]  James H. Cross,et al.  Reverse engineering and design recovery: a taxonomy , 1990, IEEE Software.

[15]  Koen Kerremans,et al.  Representing Multilingual and Culture-Specific Knowledge in a VAT Regulatory Ontology: Support from the Termontography Method , 2003, OTM Workshops.

[16]  Emmanuel Nauer,et al.  Improving Case Retrieval by Enrichment of the Domain Ontology , 2011, ICCBR.

[17]  Martin L. King,et al.  Towards a Methodology for Building Ontologies , 1995 .

[18]  H. Lan,et al.  SWRL : A semantic Web rule language combining OWL and ruleML , 2004 .

[19]  Amr Badr,et al.  A Methodology for Ontology Building , 2012 .

[20]  Mohammed Elmogy,et al.  A diabetes diagnostic domain ontology for CBR system from the conceptual model of SNOMED CT , 2014, 2014 International Conference on Engineering and Technology (ICET).

[21]  Pedro A. González-Calero,et al.  jcolibri2: A framework for building Case-based reasoning systems , 2014, Sci. Comput. Program..

[22]  Mei-Ling Huang,et al.  Usage of Case-Based Reasoning, Neural Network and Adaptive Neuro-Fuzzy Inference System Classification Techniques in Breast Cancer Dataset Classification Diagnosis , 2012, Journal of Medical Systems.

[23]  Clare Martin,et al.  An ontology of diabetes self management , 2011, MIXHS '11.

[24]  Asunción Gómez-Pérez,et al.  Ontological Reengineering for Reuse , 1999, EKAW.

[25]  A. Jaya A Standard Methodology for the Construction of Symptoms Ontology for Diabetes Diagnosis , 2011 .

[26]  Asunción Gómez-Pérez,et al.  The NeOn Methodology for Ontology Engineering , 2012, Ontology Engineering in a Networked World.

[27]  Ramanathan V. Guha,et al.  Building Large Knowledge-Based Systems: Representation and Inference in the Cyc Project , 1990 .

[28]  Asma A. Al Jarullah Decision tree discovery for the diagnosis of type II diabetes , 2011, 2011 International Conference on Innovations in Information Technology.

[29]  Elena Paslaru Bontas Simperl,et al.  Human Intelligence in the Process of Semantic Content Creation , 2010, World Wide Web.

[30]  Asunción Gómez-Pérez,et al.  Ontological Engineering: With Examples from the Areas of Knowledge Management, e-Commerce and the Semantic Web , 2004, Advanced Information and Knowledge Processing.

[31]  Robert M. MacGregor,et al.  Building and (re)using an ontology of air campaign planning , 1999, IEEE Intell. Syst..

[32]  Jie Hu,et al.  A CBR system for injection mould design based on ontology: A case study , 2012, Comput. Aided Des..

[33]  Aida Mustapha,et al.  An Analysis of Ontology Engineering Methodologies: A Literature Review , 2013 .

[34]  Sheng-Yuan Yang Developing an energy-saving and case-based reasoning information agent with Web service and ontology techniques , 2013, Expert Syst. Appl..

[35]  Jose Manuel Corera,et al.  Building and Reusing Ontologies for Electrical Network Applications , 1996, ECAI.

[36]  Yu Lin,et al.  Ontology driven modeling for the knowledge of genetic susceptibility to disease. , 2009, The Kobe journal of medical sciences.

[37]  Asma A. Al Jarullah,et al.  Decision tree discovery for the diagnosis of type II diabetes , 2011, IIT 2011.

[38]  Ian Horrocks,et al.  DAML+OIL is not Enough , 2001, SWWS.

[39]  Peter F. Patel-Schneider,et al.  OWL 2 Web Ontology Language , 2009 .

[40]  Nicholas John Kings,et al.  Semantic Web for Knowledge Sharing , 2009, Semantic Knowledge Management.

[41]  Σωτήριος Μπατσάκης SOWL: a framework for handling spatio-temporal information in OWL , 2011 .

[42]  Laia Subirats,et al.  An Ontology for Computer-Based Decision Support in Rehabilitation , 2011, MICAI.

[43]  Paola Velardi,et al.  TermExtractor: a Web Application to Learn the Common Terminology of Interest Groups and Research Communities , 2007 .

[44]  Diego Calvanese,et al.  A Framework for Ontology Integration , 2001, The Emerging Semantic Web.

[45]  Mohammed Elmogy,et al.  Electronic Health Record Data Model Optimized for Knowledge Discovery , 2012 .

[46]  Mustapha Bourahla,et al.  From UML Class Diagrams to OWL Ontologies: A Graph Transformation Based Approach , 2012, ICWIT.

[47]  Hector A. Duran-Limon,et al.  A method for building ontology-based electronic document management systems for quality standards—the case study of the ISO/TS 16949:2002 automotive standard , 2012, Applied Intelligence.

[48]  R. Subhashini A SURVEY ON ONTOLOGY CONSTRUCTION METHODOLOGIES , 2011 .

[49]  N. F. Noy,et al.  Ontology Development 101: A Guide to Creating Your First Ontology , 2001 .

[50]  Michael Gruninger,et al.  Methodology for the Design and Evaluation of Ontologies , 1995, IJCAI 1995.

[51]  Jian-xun Chen,et al.  Diabetes care decision support system , 2010, 2010 2nd International Conference on Industrial and Information Systems.

[52]  Luo Yan,et al.  Comparative Research on Methodologies for Domain Ontology Development , 2011, ICIC.

[53]  Russell Greiner,et al.  D. B. Lenat and R. V. Guha, Building Large Knowledge-Based Systems: Representation and Inference in the Cyc Project , 1993, Artif. Intell..

[54]  Roque Marín,et al.  Case representation ontology for case retrieval systems in medical domains , 2007, Artificial Intelligence and Applications.

[55]  Robert Meersman,et al.  The Use of Lexicons and Other Computer-Linguistic Tools in Semantics, Design and Cooperation of Database Systems , 1999, CODAS.

[56]  Baisakhi Chakraborty,et al.  Diabetes Detection and Care Applying CBR Techniques , 2012 .

[57]  Kalpdrum Passi,et al.  Semantic Web and Ontology Engineering for the Colorectal Cancer Follow-Up Clinical Practice Guidelines , 2013, HIS.

[58]  Vladan Devedzic,et al.  Converting UML to OWL ontologies , 2004, WWW Alt. '04.

[59]  Asunción Gómez-Pérez,et al.  METHONTOLOGY: From Ontological Art Towards Ontological Engineering , 1997, AAAI 1997.

[60]  Robert Meersman,et al.  Ontology Engineering - The DOGMA Approach , 2008, Advances in Web Semantics I.

[61]  Lisa L Hunter,et al.  Clinical Practice Guideline , 2016, Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery.

[62]  Dominique Lenne,et al.  Heterogeneity in Ontological CBR Systems , 2010 .

[63]  Changyong Liang,et al.  Intelligent Technique for Knowledge Reuse of Dental Medical Records Based on Case-Based Reasoning , 2010, Journal of Medical Systems.

[64]  Núria Casellas,et al.  Methodologies, Tools and Languages for Ontology Design , 2011 .