A Neuro-Fuzzy Approach to Diagnosis of Neonatal Jaundice

Author

Sohani, Mohammad ; Riazati, Ali ; Kermani, Kamran Kahosrovian ; Sadati, Nasser ; Makki, Behrooz

Author_Institution

Dept. of Electr. Eng., Sharif Univ. of Technol., Tehran

fYear

2006

fDate

11-13 Dec. 2006

Firstpage

1

Lastpage

4

Abstract

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

Keywords

fuzzy logic; fuzzy neural nets; learning (artificial intelligence); medical diagnostic computing; paediatrics; patient diagnosis; clinical methods; fuzzy logic system; fuzzy neural network; medical diagnosis; neonatal jaundice; neuro-fuzzy system; Biomedical engineering; Blood; Fuzzy logic; Fuzzy neural networks; Fuzzy systems; Liver diseases; Medical diagnosis; Medical diagnostic imaging; Pediatrics; Uncertainty; Diagnosis System; Evolutionary Fuzzy Neural Network; Neonatal Jaundice;

fLanguage

English

Publisher

ieee

Conference_Titel

Bio-Inspired Models of Network, Information and Computing Systems, 2006. 1st

Conference_Location

Madonna di Campiglio

Print_ISBN

1-4244-0538-6

Electronic_ISBN

1-4244-0539-4

Type

conf

DOI

10.1109/BIMNICS.2006.361808

Filename

4205335