Zobrazeno 1 - 10
of 28
pro vyhledávání: '"Mengchun G"'
Publikováno v:
Health Care Science, Vol 3, Iss 5, Pp 365-369 (2024)
Externí odkaz:
https://doaj.org/article/276b2a5c4d7c4190a8421031389cba10
Autor:
Sihui Luo, Xueying Zheng, Wei Bao, Sheng Nie, Yu Ding, Tong Yue, Yilun Zhou, Ying Hu, Hua Li, Qiongqiong Yang, Qijun Wan, Bicheng Liu, Hong Xu, Guisen Li, Gang Xu, Chunbo Chen, Huafeng Liu, Yongjun Shi, Yan Zha, Yaozhong Kong, Guobin Su, Ying Tang, Mengchun Gong, Linong Ji, Fan Fan Hou, Jianping Weng
Publikováno v:
Signal Transduction and Targeted Therapy, Vol 9, Iss 1, Pp 1-7 (2024)
Abstract Early insulin therapy is capable to achieve glycemic control and restore β-cell function in newly diagnosed type 2 diabetes (T2D), but its effect on cardiovascular outcomes in these patients remains unclear. In this nationwide real-world st
Externí odkaz:
https://doaj.org/article/fc23eb834aa14107941e6b3a4e9db4c9
Autor:
Guang-Wei Zhang, Bin Li, Zheng-Min Gu, Wei-Feng Yang, Yi-Ran Wang, Hui-Jun Li, Han-Bing Zheng, Ying-Xu Yue, Kui-Zhong Wang, Mengchun Gong, Da-Xin Gong
Publikováno v:
Journal of Medical Internet Research, Vol 26, p e54018 (2024)
BackgroundInternet hospitals (IHs) have rapidly developed as a promising strategy to address supply-demand imbalances in China’s medical industry, with their capabilities directly dependent on information platform functionality. Furthermore, a nove
Externí odkaz:
https://doaj.org/article/ae995e099f164fe78eb132c09dd59338
Publikováno v:
Journal of Medical Internet Research, Vol 26, p e46455 (2024)
BackgroundPregnancy and gestation information is routinely recorded in electronic medical record (EMR) systems across China in various data sets. The combination of data on the number of pregnancies and gestations can imply occurrences of abortions a
Externí odkaz:
https://doaj.org/article/9942b890584945479be5033650d68e41
Autor:
Yu-Qing Cai, Da-Xin Gong, Li-Ying Tang, Yue Cai, Hui-Jun Li, Tian-Ci Jing, Mengchun Gong, Wei Hu, Zhen-Wei Zhang, Xingang Zhang, Guang-Wei Zhang
Publikováno v:
Journal of Medical Internet Research, Vol 26, p e47645 (2024)
In recent years, there has been explosive development in artificial intelligence (AI), which has been widely applied in the health care field. As a typical AI technology, machine learning models have emerged with great potential in predicting cardiov
Externí odkaz:
https://doaj.org/article/11e25dbca702436f9f1e4a091440c47e
Autor:
Yue Cai, Yu-Qing Cai, Li-Ying Tang, Yi-Han Wang, Mengchun Gong, Tian-Ci Jing, Hui-Jun Li, Jesse Li-Ling, Wei Hu, Zhihua Yin, Da-Xin Gong, Guang-Wei Zhang
Publikováno v:
BMC Medicine, Vol 22, Iss 1, Pp 1-18 (2024)
Abstract Background A comprehensive overview of artificial intelligence (AI) for cardiovascular disease (CVD) prediction and a screening tool of AI models (AI-Ms) for independent external validation are lacking. This systematic review aims to identif
Externí odkaz:
https://doaj.org/article/3cb1606e112c47adab33f9058c72e113
Autor:
You Wu, Xiaoru Feng, Mengchun Gong, Jinming Han, Yuanshi Jiao, Shenglong Li, Tong Li, Chen Shen, Huai‐Yu Wang, Xinyu Yu, Zeyu Zhang, Zhengdong Zhang, Yuanfei Zhao, Peng Zhou, Haibo Wang, Zongjiu Zhang
Publikováno v:
Health Care Science, Vol 2, Iss 3, Pp 135-152 (2023)
Abstract Since the identification of the first case of pneumonia of unknown cause in 2019, the COVID‐19 pandemic has spread the globe for over 3 years. As the most populous country in the world, China's disease prevention policies and response plan
Externí odkaz:
https://doaj.org/article/8ed33f80dcfb48d68f1f58b8b1e1346b
Autor:
Changwei Wu, Yun Zhang, Sheng Nie, Daqing Hong, Jiajing Zhu, Zhi Chen, Bicheng Liu, Huafeng Liu, Qiongqiong Yang, Hua Li, Gang Xu, Jianping Weng, Yaozhong Kong, Qijun Wan, Yan Zha, Chunbo Chen, Hong Xu, Ying Hu, Yongjun Shi, Yilun Zhou, Guobin Su, Ying Tang, Mengchun Gong, Li Wang, Fanfan Hou, Yongguo Liu, Guisen Li
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-9 (2023)
Abstract Acute kidney injury (AKI) is prevalent and a leading cause of in-hospital death worldwide. Early prediction of AKI-related clinical events and timely intervention for high-risk patients could improve outcomes. We develop a deep learning mode
Externí odkaz:
https://doaj.org/article/9b8c67567b52402a9496369c0d536a67
Autor:
Lianghong Lin, Likeng Liang, Maojie Wang, Runyue Huang, Mengchun Gong, Guangjun Song, Tianyong Hao
Publikováno v:
Cancer Innovation, Vol 2, Iss 3, Pp 219-232 (2023)
Abstract With the progress and development of computer technology, applying machine learning methods to cancer research has become an important research field. To analyze the most recent research status and trends, main research topics, topic evoluti
Externí odkaz:
https://doaj.org/article/afd93b35bf344995816525e31a901580
Autor:
Mingjing Pi, Sheng Nie, Licong Su, Yanqin Li, Yue Cao, Peiyan Gao, Yuxin Lin, yan zha, Yongjun Shi, Hua Li, Jiajun Zhao, Yaozhong Kong, Guisen Li, Ying Hu, Huafeng Liu, Qijun Wan, Chunbo Chen, Bicheng Liu, Qiongqiong Yang, Guobin Su, Yilun Zhou, Jianping Weng, Gang Xu, Hong Xu, Ying Tang, Mengchun Gong, Fan Fan Hou, Xin Xu
Publikováno v:
Kidney Diseases (2023)
Introduction: Comprehensive data on the risk of hospital-acquired (HA) acute kidney injury (AKI) among adult users of opioid analgesics are lacking. This study aimed to systematically compare the risk of HA-AKI among the users of various opioid analg
Externí odkaz:
https://doaj.org/article/661ad8f167a646039c23c398361aa0a2