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Bo Hu
Researcher at Wuhan University
Publications - 13
Citations - 18740
Bo Hu is an academic researcher from Wuhan University. The author has contributed to research in topics: Medicine & Internal medicine. The author has an hindex of 4, co-authored 4 publications receiving 14922 citations.
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Journal ArticleDOI
Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China.
Dawei Wang,Bo Hu,Chang Hu,Fangfang Zhu,Xing Liu,Jing Zhang,Binbin Wang,Hui Xiang,Zhenshun Cheng,Yong Xiong,Yan Zhao,Yirong Li,Xinghuan Wang,Zhiyong Peng +13 more
TL;DR: The epidemiological and clinical characteristics of novel coronavirus (2019-nCoV)-infected pneumonia in Wuhan, China, and hospital-associated transmission as the presumed mechanism of infection for affected health professionals and hospitalized patients are described.
Journal ArticleDOI
A rapid advice guideline for the diagnosis and treatment of 2019 novel coronavirus (2019-nCoV) infected pneumonia (standard version)
Ying Hui Jin,Lin Cai,Zhen Shun Cheng,Hong Cheng,Tong Deng,Tong Deng,Yi Pin Fan,Cheng Fang,Di Huang,Lu Qi Huang,Qiao Huang,Yong Han,Bo Hu,Fen Hu,Bing Hui Li,Bing Hui Li,Yi Rong Li,Ke Liang,Likai Lin,Li Sha Luo,Jing Ma,Lin Lu Ma,Zhi Yong Peng,Yunbao Pan,Zhen Yu Pan,Xue Qun Ren,Hui Min Sun,Ying Wang,Yun Yun Wang,Hong Weng,Chao Jie Wei,Dongfang Wu,Jian Xia,Yong Xiong,Haibo Xu,Xiao Mei Yao,Yu Feng Yuan,Tai Sheng Ye,Xiaochun Zhang,Ying Wen Zhang,Yin Gao Zhang,Hua Min Zhang,Yan Zhao,Ming Juan Zhao,Hao Zi,Hao Zi,Xian Tao Zeng,Yong Yan Wang,Xinghuan Wang +48 more
TL;DR: This rapid advice guideline is suitable for the first frontline doctors and nurses, managers of hospitals and healthcare sections, community residents, public health persons, relevant researchers, and all person who are interested in the 2019-nCoV.
Journal ArticleDOI
Clinical course and outcome of 107 patients infected with the novel coronavirus, SARS-CoV-2, discharged from two hospitals in Wuhan, China.
Dawei Wang,Yimei Yin,Chang Hu,Xing Liu,Xingguo Zhang,Shuliang Zhou,Mingzhi Jian,Haibo Xu,John R. Prowle,Bo Hu,Yirong Li,Zhiyong Peng +11 more
TL;DR: A period of 7–13 days after illness onset is the critical stage in the COVID-19 course, which shows persistent lymphopenia, severe acute respiratory dyspnea syndrome, refractory shock, anuric acute kidney injury, coagulopathy, thrombocytopenia, and death.
Journal ArticleDOI
Interpretable Machine Learning for Early Prediction of Prognosis in Sepsis: A Discovery and Validation Study
TL;DR: In this article , a machine learning model based on clinical features for early predicting in-hospital mortality in critically ill patients with sepsis was developed and validated using the SHapley additive explanations (SHAP) method.
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Explainable Machine-Learning Model for Prediction of In-Hospital Mortality in Septic Patients Requiring Intensive Care Unit Readmission
TL;DR: In this article , the authors developed and validated a machine learning (ML) model for predicting in-hospital mortality in septic patients readmitted to the ICU using routinely available clinical data, and the model with the best accuracy and area under the curve (A.C.) in the validation cohort was defined as the optimal model and was selected for further prediction studies.