Abstract: In this study, designed an intelligent model for liver disorders based on Fuzzy Neural System (FNS) models is considered. For this purpose, fuzzy system and neural networks (FNS) are explored for the detection of liver disorders. The structure and learning algorithm of the FNS are described. In this study, we utilized dataset extracted from a renowned machine learning data base (UCI) repository. 10 folds cross-validation approach was explored for the design of the system. The designed algorithm is accurate, reliable and faster as compared to other traditional diagnostic systems. We highly recommend this framework as a specialized training tool for medical practitioners.

Mohammad Khaleel Sallam Ma’aitah, Rahib Abiyev and Idoko John Bush. “Intelligent Classification of Liver Disorder using Fuzzy Neural System”. International Journal of Advanced Computer Science and Applications (IJACSA) 8.12 (2017). http://dx.doi.org/10.14569/IJACSA.2017.081204

@article{Ma’aitah2017,
title = {Intelligent Classification of Liver Disorder using Fuzzy Neural System},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2017.081204},
url = {http://dx.doi.org/10.14569/IJACSA.2017.081204},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {12},
author = {Mohammad Khaleel Sallam Ma’aitah and Rahib Abiyev and Idoko John Bush}
}