A Design of Hybrid Expert System for Diagnosis of Breast Cancer and Liver Disorder

Abstract

It is certain that accurately and timely diagnosis of the diseases reduces the risk of morbidity and mortality of the disease. At that point, an expert system based on artificial intelligence techniques helps physicians or other healthcare professionals for diagnosis of it. In this study an expert system based on Firefly Algorithm is developed to diagnose both breast cancer and liver disorder. An experiential labour of the proposed system was managed using Indian Liver Patient Dataset and Breast Cancer Wisconsin (Original) Data Set received from UCI Machine Learning Repository sites. Standard statistical Metrics which are Negative Predictive Value, Positive Predictive Value, Specificity, Sensitivity, Precision, F_Measure and Accuracy are used to evaluate the performance of the proposed systems and simulation results show that the proposed system is 92% efficient in providing accurate diagnosis of Liver Disorder and 94.81% efficient in providing accurate diagnosis of Breast Cancer. C# programming language is used for the implementations of the system.

Keywords

• Firefly algorithm,Expert system,Breast cancer,Liver disorder

References

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