Showing 21 - 40 results of 93 for search '"Hebei"', query time: 0.06s Refine Results
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    Nomograms based on ratio indexes to predict severity and prognosis in immune checkpoint inhibitors-related myocarditis: a retrospective analysis by Zhenli Li, Tiezhu Yao, Guang Liu, Zhengkun Guan, Jing Liu, Ling Guo, Jingtao Ma

    Published 2024-05-01
    “…Methods We retrospectively examined patients with advanced cancers who were also diagnosed with ICI-M at the Fourth Hospital of Hebei Medical University. The patients of ICI-M were divided into mild and severe groups and a 40-day following up was carried out. …”
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    Investigating the Use of Generative Adversarial Networks-Based Deep Learning for Reducing Motion Artifacts in Cardiac Magnetic Resonance by Ma ZP, Zhu YM, Zhang XD, Zhao YX, Zheng W, Yuan SR, Li GY, Zhang TL

    Published 2025-02-01
    “…Ze-Peng Ma,1,2,* Yue-Ming Zhu,3,* Xiao-Dan Zhang,4 Yong-Xia Zhao,1 Wei Zheng,3 Shuang-Rui Yuan,1 Gao-Yang Li,1 Tian-Le Zhang1 1Department of Radiology, Affiliated Hospital of Hebei University/ Clinical Medical College, Hebei University, Baoding, 071000, People’s Republic of China; 2Hebei Key Laboratory of Precise Imaging of inflammation Tumors, Baoding, Hebei Province, 071000, People’s Republic of China; 3College of Electronic and Information Engineering, Hebei University, Baoding, Hebei Province, 071002, People’s Republic of China; 4Department of Ultrasound, Affiliated Hospital of Hebei University, Baoding, Hebei Province, 071000, People’s Republic of China*These authors contributed equally to this workCorrespondence: Xiao-Dan Zhang, Department of Ultrasound, Affiliated Hospital of Hebei University, No. 212 of Yuhua East Road, Lianchi District, Baoding, 071000, People’s Republic of China, Tel +86 17325535302, Email xiaodanzhangzxd@126.comObjective: To evaluate the effectiveness of deep learning technology based on generative adversarial networks (GANs) in reducing motion artifacts in cardiac magnetic resonance (CMR) cine sequences.Methods: The training and testing datasets consisted of 2000 and 200 pairs of clear and blurry images, respectively, acquired through simulated motion artifacts in CMR cine sequences. …”
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    Sources, Compositions, and Health Risks of PM2.5-bound PAHs at the Rural Area along with the “Coal to Gas” Law by Zhiyong Li, Ziyuan Yue, Wenjia Zhu, Wenquan Liu, Jintao Gao, Jiaqiang Zhang, Ziyi Zhan, Lan Chen, Huiying Gao, Jihong Wei

    Published 2022-12-01
    “…Here, we deployed an intensive observation in winter of 2020 at a rural site in the central area of the Beijing-Tianjin-Hebei (BTH) region. A positive matrix factorization (PMF) model and an incremental lifetime cancer risk (ILCR) model were utilized to examine the PAH sources and health risks. …”
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    Impacts of the “Coal to Gas” Policy on Rural Air VOC Level and Ozone Potentials in North China by Zhiyong Li, Chen Liu, Chengjing Cao, Zhen Zhai, Changtao Huang, Zhuangzhuang Ren, Jixiang Liu, Lan Chen, Songtao Guo, Dingyuan Yang

    Published 2023-08-01
    “…Abstract A unique study was enacted during the heating season (HS) in 2020 and 2021 at a rural site in the Beijing-Tianjin-Hebei region to evaluate the policy impacts of “Coal to Gas” (CTG) on ambient volatile organic compounds (VOCs). …”
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