Recent Study on Breast Cancer Prediction Based on Deep Neural Network Model Implemented AWS Machine Learning Platform | Chapter 3 | Advanced Aspects of Engineering Research Vol. 11

 Breast cancer is one of the most severe tumours in women, and developing breast tissue can result in mortality. Surgery, radiation, chemicals in combination with hormone therapy, and biological therapy are only a few of the current treatments for breast cancer that have shown to be effective. This paper compares the Deep Neural Network (DNN) model to other machine learning approaches such as XGBoost and Random Forest on a public dataset using the AWS machine learning framework. The plot of model accuracy for the training and validation sets, as well as performance assessment metrics to evaluate the model, reveal that the DNN model with Hyperparameter tweaking produces the best results for breast cancer prediction.

Author (s) Details

Le Dinh Phu Cuong
College of Computer Science and Electronic Engineering, Hunan University, Changsha 410082, China and Yersin University, Vietnam.

Dong Wang
College of Computer Science and Electronic Engineering, Hunan University, Changsha 410082, China.

Duyen The Hoang
College of Computer Science and Electronic Engineering, Hunan University, Changsha 410082, China.

Le Mai Nhu Uyen
Yersin University, Vietnam and College of Life Science, Hunan Normal University, Changsha 410082, China.

View Book : https://stm.bookpi.org/AAER-V11/article/view/1244