Showing 101 - 120 results of 827 for search '"Xuzhou"', query time: 0.05s Refine Results
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    Identification of specific risk factors and predictive analytics for cardio-cerebral arterial stenosis: a comparative study utilizing framingham risk stratification insights by Gege Zhang, Sijie Dong, Fanfan Feng, Weihao Kan, Taozhen Shi, Hongmei Ding, Ruiguo Dong

    Published 2025-02-01
    “…This retrospective study included patients admitted for ischemic stroke at the Affiliated Hospital of Xuzhou Medical University from December 2020 to December 2021. …”
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    The effect of preoperative topical magnesium sulfate spraying in the oropharyngeal region on postoperative sore throat following gynecological laparoscopic surgery: a randomized cl... by Linxin Wang, Fangfang Li, Yuqing Liu, Xingyu Xiong, Qin Qiu, Guanglei Wang

    Published 2025-01-01
    “…Methods The study included 58 patients scheduled for gynecologic laparoscopic surgery at Xuzhou Medical University Affiliated Hospital. Patients were randomly assigned to either the magnesium sulfate group or the control group, with 29 patients in each group. …”
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    A prediction approach to COVID-19 time series with LSTM integrated attention mechanism and transfer learning by Bin Hu, Yaohui Han, Wenhui Zhang, Qingyang Zhang, Wen Gu, Jun Bi, Bi Chen, Lishun Xiao

    Published 2024-12-01
    “…Methods Numbers of COVID-19 daily confirmed cases were collected from November 1, 2022 to November 16, 2023 in Xuzhou city of China. Classical deep learning models including recurrent neural network (RNN), long and short-term memory (LSTM), gated recurrent unit (GRU) and temporal convolutional network (TCN) are initially trained, then RNN, LSTM and GRU are integrated with a new attention mechanism and transfer learning to improve the performance. …”
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    Refined Urban Functional Zones Identification via Empirical Bayesian Kriging: A POI-Weighted Scoring Innovation by Xuan Du, Yisha Pan, Xiaoyan Yang, Longgao Chen, Liangchen Liu, Ying Lin

    Published 2025-01-01
    “…This paper proposes a Point of Interest (POI)-weighted scoring method based on Empirical Bayesian Kriging (EBK), which is empirically demonstrated in Xuzhou, China. We integrate multi-source data, including remote sensing-based land use/cover information, road networks, POIs, and building geometry data, to classify UFZs based on their dependence on buildings. …”
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