Zobrazeno 1 - 10
of 30 610
pro vyhledávání: '"ZHANG, Ling"'
Video courses have become a significant component of modern education. However, the increasing demand for live streaming video courses places considerable strain on the service capabilities of campus networks. The challenges associated with live stre
Externí odkaz:
http://arxiv.org/abs/2411.06334
Autor:
Zhang, Fengling, Mitnik, Darío, Zhang, Ling, Bao, Runjia, Zhang, Wenming, Cheng, Yunxin, Hu, Ailan, Morita, Shigeru, Ding, Xiaobin, Jie, Yinxian, Liu, Haiqing
The S/XB ratios (ionization per emitted photon) allow one to relate spectroscopic emissivity measurements to the impurity influx from a localized source. In this work, we determine the tungsten influx by examining two dominant EUV (Extreme Ultraviole
Externí odkaz:
http://arxiv.org/abs/2410.02669
Autor:
Lantrip, Amy
Publikováno v:
World Literature Today, 2021 Oct 01. 95(4), 107-107.
Externí odkaz:
https://www.jstor.org/stable/10.7588/worllitetoda.95.4.0107
Autor:
Huang, Wei, Liu, Wei, Zhang, Xiaoming, Yin, Xiaoli, Han, Xu, Li, Chunli, Gao, Yuan, Shi, Yu, Lu, Le, Zhang, Ling, Zhang, Lei, Yan, Ke
The early detection and precise diagnosis of liver tumors are tasks of critical clinical value, yet they pose significant challenges due to the high heterogeneity and variability of liver tumors. In this work, a precise LIver tumor DIAgnosis network
Externí odkaz:
http://arxiv.org/abs/2407.13217
Esophageal varices (EV), a serious health concern resulting from portal hypertension, are traditionally diagnosed through invasive endoscopic procedures. Despite non-contrast computed tomography (NC-CT) imaging being a less expensive and non-invasive
Externí odkaz:
http://arxiv.org/abs/2407.13210
Prediction of genetic biomarkers, e.g., microsatellite instability and BRAF in colorectal cancer is crucial for clinical decision making. In this paper, we propose a whole slide image (WSI) based genetic biomarker prediction method via prompting tech
Externí odkaz:
http://arxiv.org/abs/2407.09540
Autor:
Guo, Guangyu, Yao, Jiawen, Xia, Yingda, Mok, Tony C. W., Zheng, Zhilin, Han, Junwei, Lu, Le, Zhang, Dingwen, Zhou, Jian, Zhang, Ling
The absence of adequately sufficient expert-level tumor annotations hinders the effectiveness of supervised learning based opportunistic cancer screening on medical imaging. Clinical reports (that are rich in descriptive textual details) can offer a
Externí odkaz:
http://arxiv.org/abs/2405.14230
We re-examine the problem of reconstructing a high-dimensional signal from a small set of linear measurements, in combination with image prior from a diffusion probabilistic model. Well-established methods for optimizing such measurements include pri
Externí odkaz:
http://arxiv.org/abs/2405.17456
Medical Vision-Language Pretraining (Med-VLP) establishes a connection between visual content from medical images and the relevant textual descriptions. Existing Med-VLP methods primarily focus on 2D images depicting a single body part, notably chest
Externí odkaz:
http://arxiv.org/abs/2404.15272
Autor:
Cao, Weiwei, Zhang, Jianpeng, Xia, Yingda, Mok, Tony C. W., Li, Zi, Ye, Xianghua, Lu, Le, Zheng, Jian, Tang, Yuxing, Zhang, Ling
Radiologists highly desire fully automated versatile AI for medical imaging interpretation. However, the lack of extensively annotated large-scale multi-disease datasets has hindered the achievement of this goal. In this paper, we explore the feasibi
Externí odkaz:
http://arxiv.org/abs/2404.04936