no code implementations • 14 Nov 2023 • Hao Quan, Xinjia Li, Dayu Hu, Tianhang Nan, Xiaoyu Cui
The approach enhances the versatility of prototype representations and elevates the efficacy of prototype networks in few-shot pathological image classification tasks.
no code implementations • 16 Dec 2022 • Yuyang Chen, Xiaoyu Cui, Yunjie Song, Manli Wu
This study verified the effectiveness of Donald Trump's Twitter campaign in guiding agen-da-setting and deflecting political risk and examined Trump's Twitter communication strategy and explores the communication effects of his tweet content during Covid-19 pandemic.
1 code implementation • 18 May 2022 • Hao Quan, Xingyu Li, Weixing Chen, Qun Bai, Mingchen Zou, Ruijie Yang, Tingting Zheng, Ruiqun Qi, Xinghua Gao, Xiaoyu Cui
Based on digital pathology slice scanning technology, artificial intelligence algorithms represented by deep learning have achieved remarkable results in the field of computational pathology.
no code implementations • 5 May 2022 • Tingting Zheng, Weixing Chen, Shuqin Li, Hao Quan, Qun Bai, Tianhang Nan, Song Zheng, Xinghua Gao, Yue Zhao, Xiaoyu Cui
Inspired by the pathologist's clinical diagnosis process, we propose a weakly supervised deep reinforcement learning framework, which can greatly reduce the time required for network inference.
no code implementations • 1 Nov 2020 • Fengying Che, Ruichuan Shi, Jian Wu, Haoran Li, Shuqin Li, Weixing Chen, Hao Zhang, Zhi Li, Xiaoyu Cui
The feature extraction methods of radiomics are mainly based on static tomographic images at a certain moment, while the occurrence and development of disease is a dynamic process that cannot be fully reflected by only static characteristics.