Evaluation Of Machine Learning Classifiers In Breast Cancer Diagnosis

Abstract

Breast Cancer is one among the most deadly diseases that threaten women. It affects women in general but men are also not exceptions to it. Most breast cancers end up fatal except for a few cases. Early diagnosis of the disease helps in successful treatment and cure. Computer Aided Detection (CADe) or Computer Aided Diagnosis (CADx) System helps physicians to take prompt decisions in the field of medical imaging. CAD systems are aimed at identifying the abnormalities at the earliest in the human body which a human professional may fail to detect. Machine learning techniques in the field of medical imaging are increasingly being used in the accurate diagnosis of breast cancer. Machine learning classifiers such as Support Vector Machine and Neural Network are examined in this paper. Breast mammogram images, both normal and pathological images were used in this experiment. The machine learning classifiers were employed to identify the given image as either Benign ore Malignant. Performance of both the classifiers was recorded and it was observed that the Neural Network classifier excelled in the diagnosis with 98% accuracy than the Support Vector Machine classifier.