中文版 | English

在结果中检索

CASIA OpenIR

浏览/检索结果: 共33条，第1-10条 帮助

限定条件    
已选(0)清除 条数/页：   排序方式：
Explainable, Domain-Adaptive, and Federated Artificial Intelligence in Medicine 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 4, 页码: 859-876
作者:  Ahmad Chaddad;  Qizong Lu;  Jiali Li;  Yousef Katib;  Reem Kateb;  Camel Tanougast;  Ahmed Bouridane;  Ahmed Abdulkadir
Adobe PDF(6028Kb)  |  收藏  |  浏览/下载：491/358  |  提交时间：2023/03/22
Domain adaptation  explainable artificial intelligence  federated learning  
A Deep Learning Approach for Semantic Analysis of COVID-19-Related Stigma on Social Media 期刊论文
IEEE Transactions on Computational Social Systems, 2023, 页码: 246-254
作者:  Liu, Lin;  Cao, Zhidong;  Zhao, Pengfei;  Paul Jen-Hwa Hu;  Zeng, Dajun;  Luo, Yin
Adobe PDF(2871Kb)  |  收藏  |  浏览/下载：90/25  |  提交时间：2023/05/30
Coronavirus disease of 2019 (COVID-19)  deep learning  public sentiment analysis  social media  social stigma  
Future trajectory of respiratory infections following the COVID-19 pandemic in Hong Kong 期刊论文
CHAOS, 2023, 卷号: 33, 期号: 1, 页码: 8
作者:  Cheng, Weibin;  Zhou, Hanchu;  Ye, Yang;  Chen, Yifan;  Jing, Fengshi;  Cao, Zhidong;  Zeng, Daniel Dajun;  Zhang, Qingpeng
收藏  |  浏览/下载：216/0  |  提交时间：2023/03/20
Multitask Learning with Multiscale Residual Attention for Brain Tumor Segmentation and Classification 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 6, 页码: 897-908
作者:  Gaoxiang Li;  Xiao Hui;  Wenjing Li;  Yanlin Luo
Adobe PDF(2873Kb)  |  收藏  |  浏览/下载：4/1  |  提交时间：2024/04/23
Brain tumor segmentation and classification, multitask learning, multiscale residual attention module (MRAM), dynamic weight training, prior knowledge  
Pre-training in Medical Data: A Survey 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 2, 页码: 147-149
作者:  Yixuan Qiu;  Feng Lin;  Weitong Chen;  Miao Xu
Adobe PDF(2262Kb)  |  收藏  |  浏览/下载：1/0  |  提交时间：2024/04/23
Medical data  pre-training  transfer learning  self-supervised learning  medical image data  electrocardiograms (ECG) data  
A Review of Predictive and Contrastive Self-supervised Learning for Medical Images 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 4, 页码: 483-513
作者:  Wei-Chien Wang;  Euijoon Ahn;  Dagan Feng;  Jinman Kim
Adobe PDF(2691Kb)  |  收藏  |  浏览/下载：6/2  |  提交时间：2024/04/23
Self-supervised learning (SSL), contrastive learning, deep learning, medical image analysis, computer vision  
Deep learning radiomics of dual-modality ultrasound images for hierarchical diagnosis of unexplained cervical lymphadenopathy 期刊论文
BMC Medicine, 2022, 卷号: 20, 期号: 1, 页码: 1-13
作者:  Zhu,Yangyang;  Meng,Zheling;  Fan,Xiao;  Duan,Yin;  Jia,Yingying;  Dong,Tiantian;  Wang,Yanfang;  Song,Juan;  Tian,Jie;  Wang,Kun;  Nie,Fang
Adobe PDF(3297Kb)  |  收藏  |  浏览/下载：227/33  |  提交时间：2022/09/19
Deep learning  Cervical lymphadenopathy  Ultrasound  Reactive hyperplasia  Tuberculous lymphadenitis  Lymphoma  Metastatic carcinoma  
A Dissemination Model Based on Psychological Theories in Complex Social Networks 期刊论文
IEEE Transactions on Cognitive and Developmental Systems, 2022, 卷号: 14, 期号: 2, 页码: 519-531
作者:  Luo, Tianyi;  Cao, Zhidong;  Zeng, Daniel;  Zhang, Qingpeng
Adobe PDF(2330Kb)  |  收藏  |  浏览/下载：224/39  |  提交时间：2022/07/12
Chest Radiographs Using a Context-Fusion Convolution Neural Network (CNN): Can It Distinguish the Etiology of Community-Acquired Pneumonia (CAP) in Children? 期刊论文
JOURNAL OF DIGITAL IMAGING, 2022, 页码: 12
作者:  Hu, Shasha;  Zhu, Yongbei;  Dong, Di;  Wang, Bei;  Zhou, Zuofu;  Wang, Chi;  Tian, Jie;  Peng, Yun
收藏  |  浏览/下载：203/0  |  提交时间：2022/07/25
Chest radiographs  Convolution neural network  Community-acquired pneumonia  Pediatric  Etiology  
Reconstruction of the Transmission Chain of COVID-19 Outbreak in Beijing's Xinfadi Market, China 期刊论文
International Journal of Infectious Diseases, 2022, 卷号: 116, 页码: 411-417
作者:  Luo, Tianyi;  Wang, Jiaojiao;  Wang, Quanyi;  Wang, Xiaoli;  Zhao, Pengfei;  Zeng, Daniel Dajun;  Zhang, Qingpeng;  Cao, Zhidong
Adobe PDF(1640Kb)  |  收藏  |  浏览/下载：162/31  |  提交时间：2022/07/12
transmission chain  data augmentation  reconstruction  COVID-19