| Revista: | Polibits |
| Base de datos: | PERIÓDICA |
| Número de sistema: | 000374537 |
| ISSN: | 1870-9044 |
| Autores: | Nieves, Juan Carlos1 Lindgren, Helena1 |
| Instituciones: | 1Umea University, Department of Computing Science, Umea, Vasterbotten. Suecia |
| Año: | 2013 |
| Periodo: | Jul-Dic |
| Número: | 48 |
| Paginación: | 39-40 |
| País: | México |
| Idioma: | Inglés |
| Tipo de documento: | Artículo |
| Enfoque: | Aplicado, descriptivo |
| Resumen en inglés | The consideration of heterogenous knowledge sources for supporting decision making is key to accomplish informed decisions, e.g., about medical diagnosis. Consequently, merging different data from different knowledge bases is a key issue for providing support for decision-making. In this paper, we explore an argumentation context approach, which follows how medical professionals typically reason, in order to merge two basic kinds of reasoning approaches based on logic programs: deductive and abductive inferences. In this setting, we introduce two kinds of argumentation frameworks: deductive argumentation frameworks and abductive argumentation frameworks. For merging these argumentation frameworks, we follow an approach based on argumentation context systems. We illustrate the approach by considering two different declarative specifications of evidence-based medical knowledge into logic programs in order to support informed medical decisions |
| Disciplinas: | Ciencias de la computación, Medicina |
| Palabras clave: | Inteligencia artificial, Diagnóstico, Representación del conocimiento, Bases de conocimiento, Fusión de datos |
| Keyword: | Computer science, Medicine, Artificial intelligence, Diagnosis, Knowledge representation, Knowledge bases, Data merging |
| Texto completo: | Texto completo (Ver HTML) |
