Zobrazeno 1 - 10
of 4 231
pro vyhledávání: '"ZHANG, Wenli"'
Autor:
Mese, Kemal, Bunz, Oskar, Volkwein, Wolfram, Vemulapalli, Sahithya P.B., Zhang, Wenli, Schellhorn, Sebastian, Heenemann, Kristin, Rueckner, Antje, Sing, Andreas, Vahlenkamp, Thomas W., Severing, Anna-Lena, Gao, Jian, Aydin, Malik, Jung, Dominik, Bachmann, Hagen S., Zänker, Kurt S., Busch, Ulrich, Baiker, Armin, Griesinger, Christian, Ehrhardt, Anja
Previous studies reported on the broad-spectrum antiviral function of heparin. Here we investigated the antiviral function of magnesium-modified heparin and found that modified heparin displayed a significantly enhanced antiviral function against hum
Externí odkaz:
https://ul.qucosa.de/id/qucosa%3A89172
https://ul.qucosa.de/api/qucosa%3A89172/attachment/ATT-0/
https://ul.qucosa.de/api/qucosa%3A89172/attachment/ATT-0/
Autor:
Li, Haoran, Shi, Haolin, Zhang, Wenli, Wu, Wenjun, Liao, Yong, Wang, Lin, Lee, Lik-hang, Zhou, Pengyuan
Text-to-3D scene generation holds immense potential for the gaming, film, and architecture sectors. Despite significant progress, existing methods struggle with maintaining high quality, consistency, and editing flexibility. In this paper, we propose
Externí odkaz:
http://arxiv.org/abs/2404.03575
Publikováno v:
JMIR Medical Informatics, Vol 9, Iss 3, p e27079 (2021)
BackgroundWuhan, China, the epicenter of the COVID-19 pandemic, imposed citywide lockdown measures on January 23, 2020. Neighboring cities in Hubei Province followed suit with the government enforcing social distancing measures to restrict the spread
Externí odkaz:
https://doaj.org/article/4c1b1938eb86464580a43f9fa88fba81
Remote photoplethysmography (rPPG) technique extracts blood volume pulse (BVP) signals from subtle pixel changes in video frames. This study introduces rFaceNet, an advanced rPPG method that enhances the extraction of facial BVP signals with a focus
Externí odkaz:
http://arxiv.org/abs/2403.09034
This study harnesses state-of-the-art AI technology for chronic disease management, specifically in detecting various mental disorders through user-generated textual content. Existing studies typically rely on fully supervised machine learning, which
Externí odkaz:
http://arxiv.org/abs/2401.12988
Depression Detection Using Digital Traces on Social Media: A Knowledge-aware Deep Learning Approach.
Autor:
Zhang, Wenli1 (AUTHOR) wlzhang@iastate.edu, Xie, Jiaheng2 (AUTHOR) jxie@udel.edu, Zhang, Zhu3 (AUTHOR) zhuzhang@uri.edu, Liu, Xiang4 (AUTHOR) dennisl@udel.edu
Publikováno v:
Journal of Management Information Systems. 2024, Vol. 41 Issue 2, p546-580. 35p.
Online healthcare consultation in virtual health is an emerging industry marked by innovation and fierce competition. Accurate and timely prediction of healthcare consultation success can proactively help online platforms address patient concerns and
Externí odkaz:
http://arxiv.org/abs/2306.03833
Effectively representing medical concepts and patients is important for healthcare analytical applications. Representing medical concepts for healthcare analytical tasks requires incorporating medical domain knowledge and prior information from patie
Externí odkaz:
http://arxiv.org/abs/2305.00553
Depression is a common disease worldwide. It is difficult to diagnose and continues to be underdiagnosed. Because depressed patients constantly share their symptoms, major life events, and treatments on social media, researchers are turning to user-g
Externí odkaz:
http://arxiv.org/abs/2303.05389
Autor:
Zhang, Wenli1, Sun, Maoyuan2, Xu, Lian1, Chen, Sijin1, Rong, Xiyue1, Wang, Junrui1, Liu, Jia1, Liu, Bo1, Xu, Jie1, Luo, Ying1, Du, Qianying1, Wang, Yi1, Liu, Yun1, Wang, Zhigang3, Ran, Haitao3, Guo, Dajing1 guodaj@hospital.cqmu.edu.cn
Publikováno v:
Small Structures. Dec2024, p1. 15p. 10 Illustrations.