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Classification of Benign and Malignant Pulmonary Nodules Based on Ensemble Convolutional Neural Network

机译：基于集合卷积神经网络的良性和恶性肺结节分类

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《Intelligence Workshop on Advanced Computational Intelligence and Intelligent Informatics;University of Electronic Science and Technology of China;Beijing Institute of Technology》||1-6|共6页
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Lei Wang; Yaping Dai; Zhiyang Jia; Yongkang Nie; Liang Liu;
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正文语种
中图分类机械学（机械设计基础理论）;
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专利

1. Incorporating automatically learned pulmonary nodule attributes into a convolutional neural network to improve accuracy of benign-malignant nodule classification [J] . Dai Yaojun, Yan Shiju, Zheng Bin, Physics in medicine and biology. . 2018,第24期

机译：将自动学习的肺结核属性纳入卷积神经网络，以提高良性恶性结节分类的准确性
2. Mobile health framework based on adaptive feature selection of deep convolutional neural network and QoS optimisation for benign-malignant lung nodule classification [J] . Xiao Wang, Huiming Gao, Juanjuan Zhao, International journal of wireless and mobile computing . 2019,第3期

机译：基于自适应特征选择的移动健康框架，对深卷积神经网络和QoS优化对良性恶性肺结节分类
3. Differentiation of Benign from Malignant Pulmonary Nodules by Using a Convolutional Neural Network to Determine Volume Change at Chest CT [J] . Radiology . 2020,第2期

机译：利用卷积神经网络来确定胸部CT的体积变化的态度从恶性肺结结分化
4. Benign and Malignant Classification Model of Pulmonary Nodules Based on Residual Neural Network [C] . Zhenzhe Lin, Guitang Wang, Qinshen Fu, International Conference on Big Data, Electronics and Communication Engineering . 2019

机译：基于残余神经网络的肺结核良性和恶性分类模型
5. Lung Nodule Classification Using Convolutional Neural Networks [D] . Wei, Qiushi. 2019

机译：肺结结使用卷积神经网络分类
6. A CAD system for pulmonary nodule prediction based on deep three-dimensional convolutional neural networks and ensemble learning [O] . Wenkai Huang, Yihao Xue, Yu Wu 2012

机译：基于深度三维卷积神经网络和集成学习的肺结节预测CAD系统
7. Benign and Malignant Classification Model of Pulmonary Nodules Based on Residual Neural Network [O] . Zhenzhe Lin, Guitang Wang, Qinshen Fu, 2019

机译：基于残余神经网络的肺结核良性和恶性分类模型

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