Fuzzy Relational Model and Genetic Algorithms for Early Detection and Diagnosis of Breast Cancer Diagnosis in Saudi Arabia

Abstract

Breast Cancer (BC), which is considered as the most implacable malignancy and the leading cause of mortality among women in general and in Saudi Arabia specially. Most of the previous work in Saudi Arabia on this subject was on epidemiology, knowledge of (BC) and practice of breast self-examination (BSE), etiological factors, metastases and rate of survival. Early detection and diagnosis of Breast Cancer (BC) is an important, real-world medical problem. In this paper, we propose a
soft computing methodology to build a Breast Cancer (BC) diagnosis system with high capabilities. We focus on combining fuzzy concepts and genetic algorithms so as to automatically produce diagnostic systems to support and assist the expert to understand, evaluate its results with high classification performance and have the possibility of attributing a confidence measure to the output diagnosis.