Prognosis of Breast Cancer using Machine Learning Techniques and Analyzing Food Habits of Pakistani Women

Abstract

Breast cancer is easily occurred in all women due to poor eating habits. The present study examined food risk factors for breast cancer, their association with quality of life and changes in eating habits. The research included 200 women data with histological confirmed invasive breast cancer. This research data consists of different food types of This study uses different Machine learning algorithms like LR, SVM, CNN, Perceptron, GB, ADA Boost, DT, RF, and Multi-perceptron are used. Everyone has different accuracy we analyzed the ADA Boost classifier has the highest accuracy which is 87.5% due to the low quantity of our data set.

Keywords: Breast Cancer, Food Habits, Prognosis, CNN, RF, ADA Boost, GB