Ovarian Cancer Diagnosis using Artificial Neural Network

Abstract

Ovarian cancer is a quiet and dangerous enemy that affects women all over the world. It needs to early diagnosis. Radiology, cardiology, and cancer are expanding ANN research. Medical research uses ANNs. Thus, a Computer Aided Diagnosis (CAD) system using ANNs to categorize ovarian cancer based on biopsy pictures is being developed. Ovarian cancer is the fifth most common disease and the seventh major cause of death among women. Many studies categorize ovarian cancer using ANN. Classification accuracy affects physicians. Better classification helps doctors choose treatments. Early and accurate diagnosis may reduce mortality. Comparing the proposed model to the other four categorization techniques. The recommended methodology classifies ovarian cancer 98.7 percent more accurately than earlier algorithms.