TY  - JOUR
T1  - A Design of Hybrid Expert System for Diagnosis of Breast Cancer and Liver Disorder
AU  - Alaybeyoglu, Aysegul
AU  - Mulayım, Naciye
PY  - 2018
DA  - August
JF  - The Eurasia Proceedings of Science Technology Engineering and Mathematics
JO  - EPSTEM
PB  - ISRES Publishing
WT  - DergiPark
SN  - 2602-3199
SP  - 345
EP  - 353
IS  - 2
LA  - en
AB  - Itis certain that accurately and timely diagnosis of the diseases reduces therisk of morbidity and mortality of the disease. At that point, an expert systembased on artificial intelligence techniques helps physicians or otherhealthcare professionals for diagnosis of it. In this study an expert systembased on Firefly Algorithm is developed to diagnose both breast cancer andliver disorder. An experiential labour of the proposed system was managed usingIndian Liver Patient Dataset and BreastCancer Wisconsin (Original) Data Set received from UCI Machine LearningRepository sites. Standard statistical Metrics which are Negative PredictiveValue, Positive Predictive Value, Specificity, Sensitivity, Precision,F_Measure and Accuracy are used to evaluate the performance of the proposedsystems and simulation results show that the proposed system is 92% efficientin providing accurate diagnosis of Liver Disorder and 94.81% efficient inproviding accurate diagnosis of Breast Cancer. C# programming language is usedfor the implementations of the system.
KW  - Firefly algorithm
KW  - Expert system
KW  - Breast cancer
KW  - Liver disorder
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UR  - https://dergipark.org.tr/en/pub/epstem/issue//455966
L1  - https://dergipark.org.tr/en/download/article-file/528351
ER  -