Histopathological Image Analysis Of Uterus Cancer

In this paper a method for examining the malignancy in uterine histopathological pictures is presented. It offers a method for classifying uterine cancer that is based on CNN and using ReduceLROnPlateaue in order to reduce the learning rate. Since there ain't much research on endometrial cancer, some assumptions are made based on previous approaches and Conv2D with sequential model is utilized to choose a preferred method and Relu is an activation function used here to minimize the error rate and for appropriate prediction. Adam is used as an optimization algorithm. This research makes a significant contribution to the field of medicine.