Knowledge engineering and management: the CommonKADS methodology
Knowledge engineering and management: the CommonKADS methodology
What Are Ontologies, and Why Do We Need Them?
IEEE Intelligent Systems
IEEE Intelligent Systems
Towards the Semantic Web: Ontology-driven Knowledge Management
Towards the Semantic Web: Ontology-driven Knowledge Management
A Multilevel Composability Model for Semantic Web Services
IEEE Transactions on Knowledge and Data Engineering
OWL rules: A proposal and prototype implementation
Web Semantics: Science, Services and Agents on the World Wide Web
Bringing semantics to web services: the OWL-S approach
SWSWPC'04 Proceedings of the First international conference on Semantic Web Services and Web Process Composition
Partitioning the UMLS semantic network
IEEE Transactions on Information Technology in Biomedicine
Combining OpenEHR Archetype Definitions with SWRL Rules --- A Translation Approach
WSKS '08 Proceedings of the 1st world summit on The Knowledge Society: Emerging Technologies and Information Systems for the Knowledge Society
The Origin, Representation, and Use of Collaboration Patterns in a Medical Community of Practice
WSKS '08 Proceedings of the 1st world summit on The Knowledge Society: Emerging Technologies and Information Systems for the Knowledge Society
Semantic information integration and question answering based on pervasive agent ontology
Expert Systems with Applications: An International Journal
Executing medical guidelines on the web: Towards next generation healthcare
Knowledge-Based Systems
Human interaction based reasoning using ontology alignment
ACE'10 Proceedings of the 9th WSEAS international conference on Applications of computer engineering
Short communication: Reasoning with part-part relations in a description logic
Knowledge-Based Systems
Virtual doctor system (VDS): medical decision reasoning based on physical and mental ontologies
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part III
Ontology-based knowledge modeling to provide decision support for comorbid diseases
KR4HC'10 Proceedings of the ECAI 2010 conference on Knowledge representation for health-care
Integrating reasoning and clinical archetypes using OWL ontologies and SWRL rules
Journal of Biomedical Informatics
Exploiting OWL reasoning services to execute ontologically-modeled clinical practice guidelines
AIME'11 Proceedings of the 13th conference on Artificial intelligence in medicine
Continuous improvement through knowledge-guided analysis in experience feedback
Engineering Applications of Artificial Intelligence
Shared decision support system on dental restoration
Expert Systems with Applications: An International Journal
Short Communication: S-Trans: Semantic transformation of XML healthcare data into OWL ontology
Knowledge-Based Systems
Engineering Applications of Artificial Intelligence
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As the number of available Web services increases there is a growing demand to realise complex business processes by combining and reusing available Web services. In this context, the Ontology Web Language for Services (OWL-S) can be used to specify semantic types of the input and output data of a Web service and its functionality. This paper uses OWL-S to describe Web services and takes advantage of a XML syntax based on the OWL Web Ontology Language to encode OWL domain ontology fragments and SWRL rule fragments as the inputs and outputs of Web services. The approach presented outlines the use of the OWL's XML presentation syntax to obtain Web services that provide reasoning support and easily deal with facts and rules. To validate the proposal, the research has focused on Clinical Practice Guidelines (GLs) related to the biomedical field. This paper highlights the benefits and drawbacks found when applying the approach to obtain Web services that are intended to be used in clinical decision-making and rely on GLs. As an example of use, this paper concentrates on a services-based application for diagnosis and clinical management of Diabetic Retinopathy, where the end-users are health professionals who are not familiarized with Semantic Web technologies.