NFSDED: Neuro-Fuzzy System to Support the Diagnosis of Epileptic Diseases
Background: this research approaches the development of a neuro-fuzzy system to support the diagnosis of epileptic diseases (NFSDED). Neuro-fuzzy systems are the most common type of artificial intelligence in medicine. The neuro-fuzzy system contains medical knowledge represented by rules, gathering...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2009 |
| País: | Brasil |
| Institución: | Universidade Federal do Rio Grande do Sul (UFRGS) |
| Repositorio: | Clinical and Biomedical Research |
| Idioma: | portugués |
| OAI Identifier: | oai:seer.ufrgs.br:article/5101 |
| Acceso en línea: | https://seer.ufrgs.br/index.php/hcpa/article/view/5101 |
| Access Level: | acceso abierto |
| Palabra clave: | Epilepsia redes neurais artificiais lógica difusa Neurologia |
| Sumario: | Background: this research approaches the development of a neuro-fuzzy system to support the diagnosis of epileptic diseases (NFSDED). Neuro-fuzzy systems are the most common type of artificial intelligence in medicine. The neuro-fuzzy system contains medical knowledge represented by rules, gathering the strength of two paradigms: artificial neural networks and fuzzy logic. Objective: the main interest of the research is to examine the applicability of the t-norms and t-conorms fuzzy arithmetical operations, implemented by fuzzy neurons. Results: show that the arithmetical operations of Einstein's Sum/Product AND/OR implemented with the fuzzy neuron proposed by Kwan-Cai obtained the highest rates of system hits, when compared to the min/max arithmetical operations |
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