Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Youpeng Hu"'
Publikováno v:
Journal of Orthopaedic Surgery and Research, Vol 18, Iss 1, Pp 1-8 (2023)
Abstract Objective To explore the safety and the mid-term efficacy of unilateral biportal endoscopic transforaminal lumbar interbody fusion (UBE-TLIF) and 3D microscope-assisted transforaminal lumbar interbody fusion (MMIS-TLIF) for treating single-s
Externí odkaz:
https://doaj.org/article/9e7a6e2720724a9097458fceff35de91
Autor:
Chaoqun Feng, Junjie Yao, Yizhou Xie, Min Zhao, Youpeng Hu, Ziang Hu, Ruoyan Li, Haoyang Wu, Yuanxin Ge, Fei Yang, Xiaohong Fan
Publikováno v:
Heliyon, Vol 10, Iss 1, Pp e24229- (2024)
Background: Plantar fasciitis (PF) is the most common cause of chronic heel pain among adults. Extracorporeal shock wave therapy (ESWT) is the recommended in the current guidelines, and the small needle-knife yields acceptable clinical effects for mu
Externí odkaz:
https://doaj.org/article/ea437413346c42988fab271324cf1cd2
Autor:
Youpeng Hu, Lianxin Li, Binxue Hong, Yizhou Xie, Tong Li, Chaoqun Feng, Fei Yang, Yehui Wang, Jie Zhang, Yang Yu, Xiaohong Fan
Publikováno v:
Frontiers in Neurology, Vol 14 (2023)
BackgroundTraumatic spinal cord injury (TSCI) is a highly fatal and disabling event, and its incidence rate is increasing in China. Therefore, we collated the epidemiological factors of TSCI in different regions of China to update the earlier systema
Externí odkaz:
https://doaj.org/article/33269bc84e7c4b959b108eb7c14085d5
Publikováno v:
IEEE Access, Vol 9, Pp 77407-77415 (2021)
Recently, recommender systems based on Graph Convolution Network (GCN) have become a research hotspot, especially in collaborative filtering. However, most GCN-based models have inferior embedding propagation mechanism, leading to low information ext
Externí odkaz:
https://doaj.org/article/93654cbef37a493e8efd4d1108d02479
Publikováno v:
IEEE Access, Vol 8, Pp 161727-161738 (2020)
Graph clustering is a fundamental task in data analysis and has attracted considerable attention in recommendation systems, mapping knowledge domain, and biological science. Because graph convolution is very effective in combining the feature informa
Externí odkaz:
https://doaj.org/article/80709615459f42f7b98c8760cdd85f31
Publikováno v:
Neural Computing and Applications. 35:2633-2646
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2b6e336c20d89fb1f0422407c09295db
https://doi.org/10.1007/s00521-022-07735-y
https://doi.org/10.1007/s00521-022-07735-y
Publikováno v:
Spine (03622436); Feb2024, Vol. 49 Issue 3, p197-207, 11p
Publikováno v:
Knowledge and Information Systems. 64:2543-2564
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::57597ef691eceb9ecc41e9773765e841
https://doi.org/10.1007/s10115-022-01714-4
https://doi.org/10.1007/s10115-022-01714-4
Publikováno v:
IEEE Access, Vol 9, Pp 77407-77415 (2021)
Recently, recommender systems based on Graph Convolution Network (GCN) have become a research hotspot, especially in collaborative filtering. However, most GCN-based models have inferior embedding propagation mechanism, leading to low information ext
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a7275e145e4d7bf298eb4425d43d118e
https://doi.org/10.1109/access.2021.3083600
https://doi.org/10.1109/access.2021.3083600
Publikováno v:
Information Systems. 109:102051
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4106af9c884e2ede58655399065318ca
https://doi.org/10.1016/j.is.2022.102051
https://doi.org/10.1016/j.is.2022.102051