中文版 | English

在结果中检索

CASIA OpenIR

浏览/检索结果: 共5条，第1-5条 帮助

限定条件    
已选(0)清除 条数/页：   排序方式：
MLDA: Multi-Loss Domain Adaptor for Cross-Session and Cross-Emotion EEG-Based Individual Identification 期刊论文
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2023, 卷号: 27, 期号: 12, 页码: 5767-5778
作者:  Miao, Yifan;  Jiang, Wanqing;  Su, Nuo;  Shan, Jun;  Jiang, Tianzi;  Zuo, Nianming
收藏  |  浏览/下载：55/0  |  提交时间：2024/03/26
Electroencephalography  Feature extraction  Task analysis  Support vector machines  Recording  Motion pictures  Brain modeling  EEG  biometric  across mental states  across time  deep learning  domain adaptation  
A Deep Learning Radiomics Model to Identify Poor Outcome in COVID-19 Patients With Underlying Health Conditions: A Multicenter Study 期刊论文
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2021, 卷号: 25, 期号: 7, 页码: 2353-2362
作者:  Wang, Siwen;  Dong, Di;  Li, Liang;  Li, Hailin;  Bai, Yan;  Hu, Yahua;  Huang, Yuanyi;  Yu, Xiangrong;  Liu, Sibin;  Qiu, Xiaoming;  Lu, Ligong;  Wang, Meiyun;  Zha, Yunfei;  Tian, Jie
Adobe PDF(3142Kb)  |  收藏  |  浏览/下载：302/63  |  提交时间：2021/11/02
COVID-19  deep learning  radiomics  prognosis  computed tomography  
CSU-Net: A Context Spatial U-Net for Accurate Blood Vessel Segmentation in Fundus Images 期刊论文
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2021, 卷号: 25, 期号: 4, 页码: 1128-1138
作者:  Bo,Wang;  Shengpei,Wang;  Shuang,Qiu;  Wei,Wei;  Haibao,Wang;  Huiguang,He
Adobe PDF(6892Kb)  |  收藏  |  浏览/下载：308/47  |  提交时间：2021/06/21
Fundus images  blood vessel segmentation  CSU-Net  feature fusion  structure loss  
Classification of Severe and Critical Covid-19 Using Deep Learning and Radiomics 期刊论文
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2020, 卷号: 24, 期号: 12, 页码: 3585-3594
作者:  Li, Cong;  Dong, Di;  Li, Liang;  Gong, Wei;  Li, Xiaohu;  Bai, Yan;  Wang, Meiyun;  Hu, Zhenhua;  Zha, Yunfei;  Tian, Jie
Adobe PDF(2325Kb)  |  收藏  |  浏览/下载：411/64  |  提交时间：2021/03/02
COVID-19  radiomics  deep learning  computed tomography (CT)  
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;  Wang, Meiyun;  Qiu, Xiaoming;  Zha, Yunfei;  Tian, Jie
Adobe PDF(4120Kb)  |  收藏  |  浏览/下载：356/63  |  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