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Joint reconstruction of neuron and ultrastructure via connectivity consensus in electron microscope volumes 期刊论文
BMC Bioinformatics, 2022, 卷号: 23, 期号: 1, 页码: 23
作者:  Hong,Bei;  Liu,Jing;  Zhai,Hao;  Liu,Jiazheng;  Shen,Lijun;  Chen,Xi;  Xie,Qiwei;  Han,Hua
Adobe PDF(3091Kb)  |  收藏  |  浏览/下载：383/87  |  提交时间：2022/11/14
Connectomics  Reconstruction  Connectivity concept  Joint optimization  Electron microscope volumes  
Deep learning for predicting immunotherapeutic efficacy in advanced non-small cell lung cancer patients: a retrospective study combining progression-free survival risk and overall survival risk 期刊论文
TRANSLATIONAL LUNG CANCER RESEARCH, 2022, 页码: 23
作者:  He, Bing-Xi;  Zhong, Yi-Fan;  Zhu, Yong-Bei;  Deng, Jia-Jun;  Fang, Meng-Jie;  She, Yun-Lang;  Wang, Ting-Ting;  Yang, Yang;  Sun, Xi-Wen;  Belluomini, Lorenzo;  Watanabe, Satoshi;  Dong, Di;  Tian, Jie;  Xie, Dong
Adobe PDF(3742Kb)  |  收藏  |  浏览/下载：375/47  |  提交时间：2022/06/10
Tumor biomarkers  immunotherapy  lung neoplasms  programmed cell death 1 receptor (PD-1 receptor)  biostatistics  
Attention Enhanced Reinforcement Learning for Multi agent Cooperation 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 页码: 15
作者:  Pu, Zhiqiang;  Wang, Huimu;  Liu, Zhen;  Yi, Jianqiang;  Wu, Shiguang
Adobe PDF(2967Kb)  |  收藏  |  浏览/下载：366/56  |  提交时间：2022/06/06
Training  Reinforcement learning  Games  Scalability  Task analysis  Standards  Optimization  Attention mechanism  deep reinforcement learning (DRL)  graph convolutional networks  multi agent systems  
Deep learning-based AI model for signet-ring cell carcinoma diagnosis and chemotherapy response prediction in gastric cancer 期刊论文
MEDICAL PHYSICS, 2022, 页码: 12
作者:  Li, Cong;  Qin, Yun;  Zhang, Wei-Han;  Jiang, Hanyu;  Song, Bin;  Bashir, Mustafa R.;  Xu, Heng;  Duan, Ting;  Fang, Mengjie;  Zhong, Lianzhen;  Meng, Lingwei;  Dong, Di;  Hu, Zhenhua;  Tian, Jie;  Hu, Jian-Kun
Adobe PDF(1878Kb)  |  收藏  |  浏览/下载：448/101  |  提交时间：2022/03/17
chemotherapy  deep learning  diagnosis  signet-ring cell carcinoma  survival