Designing a Hybrid Neuro-Fuzzy System for Classifying the Complex Data, Application on Cornea Transplant

摘要

Artificial Neural Networks are one of the Best tools for classification of complex sets of patterns. It's a crucial issue which could assist physicians to make correct decisions. In this article, a specific application of AI is applied for a biomedical engineering purpose. The aim is to find the best classifier for discriminating Lasik eyes from non- Lasik ones, using neural networks. Previously Porkar and Sedigh Fazli [8] have been showed that how HMM can optimize the traditional statics method and now for obtaining more optimized systems, we continued our researches on using Intelligent neural networks supported by fuzzy logic .Two models are applied: One is MLP which is a base model on neural network and the other classifier is a hybrid neuro-fuzzy model called LoLiMoT. This process seems to be more accurate compared to statistical ones.