Application of Deep Learning Algorithms in Diagnosis of Breast Cancer
DENG Zhuo1,2，SU Binghua1,2，ZHANG Kai1
1. Key Laboratory of Photoelectric Imaging and System, Ministry of Education, Beijing Institute of Technology
Zhuhai, Zhuhai Guangdong 519088, China| 2. Beijing Institute of Technology, Beijing100081, China
Abstract：The purpose of this article is to explore the diagnostic value of three network structures using deep learning for breast cancer tumors. Based on the three basic networks of deep neural network, convolutional neural network and recurrent neural network (RNN), this article models and classifies the difference between benign and malignant breast tumors. Furthermore, the actual breast tumor sample data of the human body was used for model parameter training, and the test set data was used to verify the model. The results showed that the three networks can identify the nature of the tumor in high accuracy, among them the accuracy of RNN was close to 100%. This research can assist doctors in improving the accuracy and efficiency of breast tumor diagnosis.
邓卓1,2，苏秉华1,2，张凯1. 深度学习算法在乳腺肿瘤诊断中的应用研究[J]. 中国医疗设备, 2020, 35(9): 60-64.
DENG Zhuo1,2，SU Binghua1,2，ZHANG Kai1. Application of Deep Learning Algorithms in Diagnosis of Breast Cancer. China Medical Devices, 2020, 35(9): 60-64.
