A Neuro-Fuzzy Approach to Diagnosis of Neonatal Jaundice

被引：0

作者：

Sohani, Mohammad ^{[1
]}

Kermani, Kamran Kahosrovian ^{[2
]}

Makki, Behrooz ^{[3
]}

Sadati, Nasser ^{[1
]}

Riazati, Ali ^{[3
]}

机构：

[1] Sharif Univ Technol, Elect Engn Dept, Tehran, Iran

[2] Amirkabir Univ Technol, Elect Engn Dept, Tehran, Iran

[3] Amirkabir Univ Technol, Biomed Engn Dept, Tehran, Iran

来源：

2006 1ST BIO-INSPIRED MODELS OF NETWORK, INFORMATION AND COMPUTING SYSTEMS | 2006年

关键词：

Evolutionary Fuzzy Neural Network; Diagnosis System; Neonatal Jaundice;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents an approach that integrates clinical methods with Neuro-Fuzzy system in order to diagnose Neonatal Jaundice in newborns. First, a fuzzy logic system designed with medical rules to model the uncertainty that exists in medical diagnosis. Then a fuzzy neural network with an evolutionary learning helps the system to learn the new data gained from the patient and to help the fuzzy system to update itself in an online manner. By combining the aforementioned systems, the proposed approach can help physicians to diagnose jaundice with low risk cost associated with this disease.

引用

页数：4

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