A Deep Learning Breast Cancer Prediction Framework

作     者：Asmaa E.E.Ali Mofreh Mohamed Salem Mahmoud Badway Ali IEL Desouky 

作者机构：Department of Computer ScienceFaculty of EngineeringMansoura UniversityMansoura35111Egypt 

出 版 物：《Journal on Artificial Intelligence》 (人工智能杂志（英文）)

年 卷 期：2021年第3卷第3期

页      面：81-96页

学科分类：1002[医学-临床医学] 100214[医学-肿瘤学] 10[医学] 

主　　题：BrC diagnosis DGCO algorithm deep recurrent neural networks classification 

摘      要：Breast cancer(BrC)is now the world’s leading cause of death for *** detection and effective treatment of this disease are the only rescues to reduce BrC *** prediction of BrC diseases is very difficult because it is not an individual disease but a mixture of various *** researchers have used different techniques such as classification,Machine Learning(ML),and Deep Learning(DL)of the prediction of the breast tumor into Benign and ***,still there is a scope to introduce appropriate techniques for developing and implementing a more effective diagnosis *** paper proposes a DL prediction BrC framework that uses a selected Bidirectional Recurrent Neural Network(BRNN).An efficient fast and accurate optimizer is needed to train the neural network *** more recent Dynamic Group-based Cooperative Optimization Group(DGCO)algorithm is modified MDGCO for this *** Deep Learning Breast Cancer Prediction Framework(DLBCPF)includes four layers:preprocessing,feature selection,optimized Recurrent Neural Networks,and *** different Wisconsin BrC datasets are used to test the validity of the proposed framework and optimizer against *** results obtained have shown the superiority of both the framework DLBCPF and the optimizer MDGCO when they are compared to others.