NFSDED: Neuro-Fuzzy System to Support the Diagnosis of Epileptic Diseases

Lucimar Fossatti de Carvalho, Hugo José Carvalho, Ciciliana Zílio Rech


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


Epilepsia; redes neurais artificiais, lógica difusa

Copyright (c)

ISSN: 2357-9730



Apoio Financeiro:


Licença Creative Commons
The Clinical & Biomedical Research is licenced under Creative Commons Atribuição 4.0 Internacional.