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...
| Authors: | , , |
|---|---|
| Format: | article |
| Status: | Published version |
| Publication Date: | 2009 |
| Country: | Brasil |
| Institution: | Universidade Federal do Rio Grande do Sul (UFRGS) |
| Repository: | Clinical and Biomedical Research |
| Language: | Portuguese |
| OAI Identifier: | oai:seer.ufrgs.br:article/5101 |
| Online Access: | https://seer.ufrgs.br/index.php/hcpa/article/view/5101 |
| Access Level: | Open access |
| Keyword: | Epilepsia redes neurais artificiais lógica difusa Neurologia |
| Summary: | 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 |
|---|