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Collective Entity Alignment for Knowledge Fusion of Power Grid Dispatching Knowledge Graphs 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2021, 卷号: 9, 期号: 11, 页码: 1-15
作者:  Yang, Linyao;  Lv, Chen;  Wang, Xiao;  Qiao, Ji;  Ding, Weiping;  Zhang, Jun;  Wang, Fei-Yue
Adobe PDF(1600Kb)  |  收藏  |  浏览/下载：217/29  |  提交时间：2022/06/15
entity alignment  integer programming  knowledge fusion  knowledge graph embedding  power dispatch  
Medical Term and Status Generation From Chinese Clinical Dialogue With Multi-Granularity Transformer 期刊论文
IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 2021, 卷号: 29, 页码: 3362-3374
作者:  Li, Mei;  Xiang, Lu;  Kang, Xiaomian;  Zhao, Yang;  Zhou, Yu;  Zong, Chengqing
Adobe PDF(3036Kb)  |  收藏  |  浏览/下载：319/72  |  提交时间：2021/12/28
Medical diagnostic imaging  Transformers  Task analysis  Medical services  Computational modeling  Semantics  Data mining  Medical dialogue  multi-granularity  attention mechanism  natural language understanding  sequence to sequence learning  
A deep learning-based radiomic nomogram for prognosis and treatment decision in advanced nasopharyngeal carcinoma: A multicentre study 期刊论文
EBIOMEDICINE, 2021, 卷号: 70, 页码: 10
作者:  Zhong, Lianzhen;  Dong, Di;  Fang, Xueliang;  Zhang, Fan;  Zhang, Ning;  Zhang, Liwen;  Fang, Mengjie;  Jiang, Wei;  Liang, Shaobo;  Li, Cong;  Liu, Yujia;  Zhao, Xun;  Cao, Runnan;  Shan, Hong;  Hu, Zhenhua;  Ma, Jun;  Tang, Linglong;  Tian, Jie
Adobe PDF(3679Kb)  |  收藏  |  浏览/下载：413/75  |  提交时间：2021/11/03
Multi-task deep learning  Radiomic nomogram  Survival analysis  Treatment decision  Advanced nasopharyngeal carcinoma  
ImmunoAIzer: A Deep Learning-Based Computational Framework to Characterize Cell Distribution and Gene Mutation in Tumor Microenvironment 期刊论文
CANCERS, 2021, 卷号: 13, 期号: 7, 页码: 21
作者:  Bian, Chang;  Wang, Yu;  Lu, Zhihao;  An, Yu;  Wang, Hanfan;  Kong, Lingxin;  Du, Yang;  Tian, Jie
Adobe PDF(14076Kb)  |  收藏  |  浏览/下载：324/32  |  提交时间：2021/05/17
deep learning  cell distribution  biomarker  tumor gene mutation  tumor microenvironment (TME)  semi-supervised learning  hematoxylin and eosin (H&  E)