A Machine Learning approach for classification of ovarian tumours

Abstract

Ovarian tumours are abnormal growths in the ovaries which can be either cancerous or non-cancerous. Ovarian cancer is reported to cause more deaths than any other female reproductive cancers. In order to reduce the death rate, early diagnosis and treatment is required. In the recent days, Artificial Intelligence (AI) based Computer Aided Diagnosis(CAD) is being used performed in order to reduce human errors. This work is one such CAD based classification system to classify of benign and malignant ovarian tumours. Six popular Machine Learning(ML) algorithms have been applied on clinical ovarian bio-markers with an aim to classify the tumours. Also, a comparative study between the applied ML techniques is given in the result and discussion section.