Autonomous Agents and Multi-Agent Systems
Proceedings of the 2008 conference on Computational Models of Argument: Proceedings of COMMA 2008
An argument-based approach to reasoning with clinical knowledge
International Journal of Approximate Reasoning
The Knowledge Engineering Review
Qualitative Evidence Aggregation using Argumentation
Proceedings of the 2010 conference on Computational Models of Argument: Proceedings of COMMA 2010
Using clinical preferences in argumentation about evidence from clinical trials
Proceedings of the 1st ACM International Health Informatics Symposium
Towards argument representational tools for hybrid argumentation systems
HCII'11 Proceedings of the 1st international conference on Human interface and the management of information: interacting with information - Volume Part II
Multi-criteria decision making in ontologies
Information Sciences: an International Journal
Aggregating evidence about the positive and negative effects of treatments
Artificial Intelligence in Medicine
ONTOarg: A decision support framework for ontology integration based on argumentation
Expert Systems with Applications: An International Journal
Argumentation-logic for creating and explaining medical hypotheses
Artificial Intelligence in Medicine
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We introduce a novel Ontology-based Argumentation Framework (OAF) that links a logic-based argumentation formalism and description logic ontologies. We show how these two formalisms can be tightly coupled by observing a few simple restrictions, and provides features not available in either formalism alone. Our work is evaluated in a large case study on decision-making in treatment choice in breast cancer, where rules are developed from the results of pub- lished clinical trials, and we present a small subset of this to demonstrate the use of the system. We show that OAF provides five advantages: (1) facilitating the clear use of shared definitions between multiple authors; (2) enabling us to match terms in the ontology and rules with those in the specific domain literature; (3) providing a close fit be- tween structure of clinical trials and the structure of our rules; (4) delivering significant economies in the size of the rule-base compared to existing approaches; (5) allowing us take advantage of developments in both ontological and ar- gumentative approaches. We also demonstrate that even a restricted language such as ours is sufficient to capture enough information to generate arguments that are useful for clinical practice. An early prototype implementation is available.