Int. J. Comput. Model. Algorithms Medicine最新文献

{"title":"Modeling a Classification Scheme of Epileptic Seizures Using Ontology Web Language","authors":"Bhaswati Ghosh, Partha Ghosh, I. Sikder","doi":"10.4018/jcmam.2010072004","DOIUrl":"https://doi.org/10.4018/jcmam.2010072004","url":null,"abstract":"Ontology-based disease classification offers a way to rigorously assign disease types and to reuse diagnostic knowledge. However, ontology itself is not sufficient for fully representing the complex knowledge needed in classification schemes which are continuously evolving. This article describes the application of SWRL/ OWL-DL to the representation of knowledge intended for proper classification of a complex neurological condition, namely epilepsy. The authors present a rigorous and expandable approach to the ontological classification of epileptic seizures based on the 1981ILAE classification. It provides a classification knowledge base that can be extended with rules that describe constraints in SWRL. Moreover, by transforming an OWL classification scheme into JESS (rule engine in Java platform) facts and by transforming SWRL constraints into JESS, logical inferences and reasoning provide a mechanism to discover new knowledge and facts. The logic representation of epileptic classification amounts to greater community understanding among practitioners, knowledge reuse and interoperability. DOI: 10.4018/jcmam.2010072004 IGI PUBLISHING This paper appears in the publication, International Journal of Computational Models and Algorithms in Medicine, Volume 1, Issue 1 edited by Aryya Gangopadhyay © 2010, IGI Global 701 E. Chocolate Avenue, Hershey PA 17033-1240, USA Tel: 717/533-8845; Fax 717/533-8661; URL-http://www.igi-global.com ITJ 5529 46 International Journal of Computational Models and Algorithms in Medicine, 1(1), 45-60, January-March 2010 Copyright © 2010, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. ent definitions of phenotypes in the literature (Mahner & Kary, 1997). To enforce semantic specification, ontology has been widely used in many clinical diagnostic decision support systems (Yu, 2006). In particular, neurology, as a subspecialty, has many native built in semantics. Additionally, neurological conditions are unique and may not be very familiar to other medical specialists. The medications prescribed by neurologists and the investigations (e.g. Electroencephalogram (EEG), Magnetic Resonance Imaging (MRI), Nerve Conduction Study/ Electromyography (NCS/ EMG) etc) are often different from other medical subspecialties. Hence, having a specialty specific ontology is essential to integrate neurology with other medical software systems. It is particularly important when developing a specific ontology system for epilepsy, a subspeciality within neurology. Epilepsy is a condition which is frequently encountered by general practitioners before these patients get referred to a neurologist. Epilepsy is a chronic neurological condition with significant morbidity and increased risk of mortality compared to the general population. Proper diagnosis and management is of essential importance not only in the short term but also for long term prognosis. In this article we prese","PeriodicalId":162417,"journal":{"name":"Int. J. Comput. Model. Algorithms Medicine","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121335821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}