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浏览/检索结果: 共6条，第1-6条 帮助 限定条件 专题：自动化研究所    第一署名单位    第一作者单位    通讯作者单位     已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择作者升序作者降序题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序 Learning to learn by yourself: Unsupervised meta-learning with self-knowledge distillation for COVID-19 diagnosis from pneumonia cases 期刊论文 INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, 2021, 页码: 32 作者:  Zheng, Wenbo;  Yan, Lan;  Gou, Chao;  Zhang, Zhi-Cheng;  Zhang, Jun J. 收藏  |  浏览/下载：33/0  |  提交时间：2021/06/15 biomedical imaging  COVID‐  19  knowledge distillation  meta‐  learning  unsupervised learning   A Deep Learning Prognosis Model Help Alert for COVID-19 Patients at High-Risk of Death: A Multi-Center Study 期刊论文 IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2020, 卷号: 24, 期号: 12, 页码: 3576-3584 作者:  Meng, Lingwei;  Dong, Di;  Li, Liang;  Niu, Meng;  Bai, Yan 收藏  |  浏览/下载：36/0  |  提交时间：2021/03/02 COVID-19  Computed tomography  Lung  Hospitals  Biomedical imaging  Training  Coronavirus disease 2019 (COVID-19)  prognosis  computed tomography  deep learning  artificial intelligence   A fully automatic deep learning system for COVID-19 diagnostic and prognostic analysis 期刊论文 EUROPEAN RESPIRATORY JOURNAL, 2020, 卷号: 56, 期号: 2, 页码: 11 作者:  Wang, Shuo;  Zha, Yunfei;  Li, Weimin;  Wu, Qingxia;  Li, Xiaohu 收藏  |  浏览/下载：26/0  |  提交时间：2020/09/21 Deep learning -based multi -view fusion model for screening 2019 novel coronavirus pneumonia: A multicentre study 期刊论文 EUROPEAN JOURNAL OF RADIOLOGY, 2020, 卷号: 128, 期号: 109041, 页码: 9 作者:  Wu, Xiangjun;  Hui, Hui;  Niu, Meng;  Li, Liang;  Wang, Li 收藏  |  浏览/下载：19/0  |  提交时间：2020/07/20 Coronavirus disease 2019  Deep learning  Multi-view model  Computed tomography   Deep learning -based multi -view fusion model for screening 2019 novel coronavirus pneumonia: A multicentre study 期刊论文 EUROPEAN JOURNAL OF RADIOLOGY, 2020, 卷号: 128, 期号: 109041, 页码: 9 作者:  Wu, Xiangjun;  Hui, Hui;  Niu, Meng;  Li, Liang;  Wang, Li 收藏  |  浏览/下载：11/0  |  提交时间：2020/07/20 Coronavirus disease 2019  Deep learning  Multi-view model  Computed tomography   Radiomics Analysis of Computed Tomography helps predict poor prognostic outcome in COVID-19 期刊论文 THERANOSTICS, 2020, 卷号: 10, 期号: 16, 页码: 7231-7244 作者:  Wu, Qingxia;  Wang, Shuo;  Liang, Li;  Wu, Qingxia;  Qian, Wei 收藏  |  浏览/下载：27/0  |  提交时间：2020/08/03 COVID-19  Computed tomography  Radiomics  Prognosis  Poor outcome