Recent Study on Breast Cancer Prediction Based on Deep Neural Network Model Implemented AWS Machine Learning Platform
Le Dinh Phu Cuong, Dong Wang, Duyen The Hoang, Le Mai Nhu Uyen · Book Publisher International (a part of SCIENCEDOMAIN International) · 2021
Breast cancer is one of the most dangerous cancers in women, with developing breast tissue leading to death. Surgery, radiation, chemicals in conjunction with hormone therapy, and biological therapy are some of the current therapies for breast cancer that have made significant progress. The Deep Neural Network (DNN) model is implemented on the AWS machine learning framework in this work, as well as a comparison with other machine learning techniques such as XGBoost and Random Forest on a public dataset. The plot of model accuracy for the training and validation sets, as well as performance assessment metrics to evaluate the model, show that breast cancer prediction based on DNN model with Hyperparameter tuning has the best results.