Breast Cancer Predictor Using Deep Learning

Abstract

Abstract:- The problem of the Breast Cancer around the world among women becoming worsens each passing day. Curing of Breast Cancer disease is never easy for women. It is also become hard when women are in there 30’s. After several researches or experiments by our doctors and scientists, there is no 100% curable treatment for the cancer. In India, in every 4 minutes one women is diagnosed with breast cancer and in every 13 minutes one women is died due to breast cancer. According to WHO report of year 2022 around 670000 people died due to breast cancer and around 2.3 million women diagnosed with this cancer. Out of 185 countries in the world women from 157 countries suffering from breast cancer. We can also say that due to lack of accurate prediction models results in the difficulty for doctors to prepare for a treatment plan. So, we are trying to develop a model by using two different approaches i.e., train and testing method and by using cross-validation method. We will discuss about which approach gives good accuracy with minimum errors in less time. We will use the algorithms like SVM, AdaBoost, XgBoost, KNN, Naïve Bayes to determine the accuracy. This work is done to predict the outcomes of different types of techniques and which technique has good accuracy, F1 score, precision, recall.