Zobrazeno 1 - 10
of 43
pro vyhledávání: '"Xiang-Tian Yu"'
Autor:
Chunchun Yuan, Xiang-Tian Yu, Jing Wang, Bing Shu, Xiao-Yun Wang, Chen Huang, Xia Lv, Qian-Qian Peng, Wen-Hao Qi, Jing Zhang, Yan Zheng, Si-Jia Wang, Qian-Qian Liang, Qi Shi, Ting Li, He Huang, Zhen-Dong Mei, Hai-Tao Zhang, Hong-Bin Xu, Jiarui Cui, Hongyu Wang, Hong Zhang, Bin-Hao Shi, Pan Sun, Hui Zhang, Zhao-Long Ma, Yuan Feng, Luonan Chen, Tao Zeng, De-Zhi Tang, Yong-Jun Wang
Publikováno v:
Cell Discovery, Vol 10, Iss 1, Pp 1-24 (2024)
Abstract Due to a rapidly aging global population, osteoporosis and the associated risk of bone fractures have become a wide-spread public health problem. However, osteoporosis is very heterogeneous, and the existing standard diagnostic measure is no
Externí odkaz:
https://doaj.org/article/abd2d89db13c428f91fbc775013421f3
Autor:
Xiang Li, Zi-Yuan Wang, Na Ren, Zhan-Ying Wei, Wei-Wei Hu, Jie-Mei Gu, Zhen-Lin Zhang, Xiang-Tian Yu, Chun Wang
Publikováno v:
Frontiers in Pharmacology, Vol 14 (2023)
Zoledronic acid (ZOL) is a potent antiresorptive agent that increases bone mineral density (BMD) and reduces fracture risk in postmenopausal osteoporosis (PMOP). The anti-osteoporotic effect of ZOL is determined by annual BMD measurement. In most cas
Externí odkaz:
https://doaj.org/article/70353156629746058f2dec2515c4ace7
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 20, Iss , Pp 5524-5534 (2022)
Gastrointestinal diseases are complex diseases that occur in the gastrointestinal tract. Common gastrointestinal diseases include chronic gastritis, peptic ulcers, inflammatory bowel disease, and gastrointestinal tumors. These diseases may manifest a
Externí odkaz:
https://doaj.org/article/cea6c1bee6484344914b3dc6627a43ec
Autor:
Huang, De-Xing, Zhou, Xiao-Hu, Gui, Mei-Jiang, Xie, Xiao-Liang, Liu, Shi-Qi, Wang, Shuang-Yi, Li, Hao, Xiang, Tian-Yu, Hou, Zeng-Guang
Iodinated contrast agents are widely utilized in numerous interventional procedures, yet posing substantial health risks to patients. This paper presents CAS-GAN, a novel GAN framework that serves as a ``virtual contrast agent" to synthesize X-ray an
Externí odkaz:
http://arxiv.org/abs/2410.08490
Autor:
Huang, De-Xing, Zhou, Xiao-Hu, Xie, Xiao-Liang, Liu, Shi-Qi, Wang, Shuang-Yi, Feng, Zhen-Qiu, Gui, Mei-Jiang, Li, Hao, Xiang, Tian-Yu, Yao, Bo-Xian, Hou, Zeng-Guang
Automatic vessel segmentation is paramount for developing next-generation interventional navigation systems. However, current approaches suffer from suboptimal segmentation performances due to significant challenges in intraoperative images (i.e., lo
Externí odkaz:
http://arxiv.org/abs/2406.19749
Autor:
Xiao-Yu Chen, Hui-Ning Fan, Huang-Kai Zhang, Huang-Wen Qin, Li Shen, Xiang-Tian Yu, Jing Zhang, Jin-Shui Zhu
Publikováno v:
Frontiers in Bioengineering and Biotechnology, Vol 8 (2020)
The development of non-invasive, inexpensive, and effective early diagnosis tests for gastric and small-bowel lesions is an urgent requirement. The introduction of magnetically guided capsule endoscopy (MGCE) has aided examination of the small bowel
Externí odkaz:
https://doaj.org/article/c4851c9230a8431491112a545c14f3c8
Autor:
Huang, De-Xing, Zhou, Xiao-Hu, Xie, Xiao-Liang, Liu, Shi-Qi, Feng, Zhen-Qiu, Gui, Mei-Jiang, Li, Hao, Xiang, Tian-Yu, Liu, Xiu-Ling, Hou, Zeng-Guang
Medical image segmentation takes an important position in various clinical applications. Deep learning has emerged as the predominant solution for automated segmentation of volumetric medical images. 2.5D-based segmentation models bridge computationa
Externí odkaz:
http://arxiv.org/abs/2401.11856
Autor:
Liu, Xiao-Yin, Zhou, Xiao-Hu, Li, Guotao, Li, Hao, Gui, Mei-Jiang, Xiang, Tian-Yu, Huang, De-Xing, Hou, Zeng-Guang
Offline reinforcement learning (RL) faces a significant challenge of distribution shift. Model-free offline RL penalizes the Q value for out-of-distribution (OOD) data or constrains the policy closed to the behavior policy to tackle this problem, but
Externí odkaz:
http://arxiv.org/abs/2312.03991
Autor:
Li, Hao, Zhou, Xiao-Hu, Xie, Xiao-Liang, Liu, Shi-Qi, Feng, Zhen-Qiu, Liu, Xiao-Yin, Gui, Mei-Jiang, Xiang, Tian-Yu, Huang, De-Xing, Yao, Bo-Xian, Hou, Zeng-Guang
Offline reinforcement learning (RL) aims to optimize policy using collected data without online interactions. Model-based approaches are particularly appealing for addressing offline RL challenges due to their capability to mitigate the limitations o
Externí odkaz:
http://arxiv.org/abs/2310.17245
Autor:
Liu, Xiao-Yin, Zhou, Xiao-Hu, Gui, Mei-Jiang, Xie, Xiao-Liang, Liu, Shi-Qi, Wang, Shuang-Yi, Li, Hao, Xiang, Tian-Yu, Huang, De-Xing, Hou, Zeng-Guang
Model-based reinforcement learning (RL), which learns environment model from offline dataset and generates more out-of-distribution model data, has become an effective approach to the problem of distribution shift in offline RL. Due to the gap betwee
Externí odkaz:
http://arxiv.org/abs/2309.08925