日期:
2020 年 — 2026 年
2020
2021
2022
2023
2024
2025
2026
影响因子:

Prediction of sepsis among patients with major trauma using artificial intelligence: a multicenter validated cohort study

利用人工智能预测重度创伤患者脓毒症:一项多中心验证队列研究

Sun, Baisheng; Lei, Mingxing; Wang, Li; Wang, Xiaoli; Li, Xiaoming; Mao, Zhi; Kang, Hongjun; Liu, Hui; Sun, Shiying; Zhou, Feihu

Epidemiological shifts and advances in research on early diagnosis of invasive fungal infection in critically ill patients

流行病学变化及危重患者侵袭性真菌感染早期诊断研究进展

Cao, Yuan; Li, Yun; Wang, Min; Wu, Yiqi; Shi, Shaoqing; Wang, Chengjin; Gao, Zhen; Yang, Wenjun; Wang, Lu; Kang, Hongjun

Accuracy of blood heparin-binding protein (HBP) for diagnosis bacteremia in patients with sepsis

血液中肝素结合蛋白(HBP)在脓毒症患者菌血症诊断中的准确性

Mao, Zhi; Yang, Wenshan; Gao, Jie; Zhang, Jingwen; Yang, Mengmeng; Liu, Hui; Kang, Hongjun; Zhou, Feihu

Machine learning model for early prediction of acute kidney injury in heatstroke patients based on the first 24 h hospitalization data

基于入院后24小时数据的机器学习模型,用于早期预测中暑患者急性肾损伤

Ding, Xiaonan; Wang, Min; Wang, Lu; Li, Yun; Yan, Lei; Li, Lu; Niu, Yue; Du, Junxia; Duan, Yingjie; Chen, Fei; Song, Chenwen; Kang, Hongjun; Zhu, Hanyu

Predicting multiple organ dysfunction syndrome in trauma-induced sepsis: Nomogram and machine learning approaches

预测创伤诱发脓毒症中的多器官功能障碍综合征:列线图和机器学习方法

Peng, Jinyu; Li, Yun; Liu, Chao; Mao, Zhi; Kang, Hongjun; Zhou, Feihu

Advances in the Application of AI Robots in Critical Care: Scoping Review

人工智能机器人在重症监护领域应用进展:范围界定综述

Li, Yun; Wang, Min; Wang, Lu; Cao, Yuan; Liu, Yuyan; Zhao, Yan; Yuan, Rui; Yang, Mengmeng; Lu, Siqian; Sun, Zhichao; Zhou, Feihu; Qian, Zhirong; Kang, Hongjun

Immunotherapy in the context of sepsis-induced immunological dysregulation

脓毒症诱发的免疫失调背景下的免疫疗法

Wu, Yiqi; Wang, Lu; Li, Yun; Cao, Yuan; Wang, Min; Deng, Zihui; Kang, Hongjun

Research advances in the function and anti-aging effects of nicotinamide mononucleotide

烟酰胺单核苷酸的功能和抗衰老作用的研究进展

Wang, Min; Cao, Yuan; Li, Yun; Wang, Lu; Liu, Yuyan; Deng, Zihui; Zhu, Lianrong; Kang, Hongjun

Development and validation of machine learning models to predict MDRO colonization or infection on ICU admission by using electronic health record data

利用电子健康记录数据,开发和验证机器学习模型,以预测ICU入院时多重耐药菌(MDRO)的定植或感染情况。

Li, Yun; Cao, Yuan; Wang, Min; Wang, Lu; Wu, Yiqi; Fang, Yuan; Zhao, Yan; Fan, Yong; Liu, Xiaoli; Liang, Hong; Yang, Mengmeng; Yuan, Rui; Zhou, Feihu; Zhang, Zhengbo; Kang, Hongjun

Predicting hypovitaminosis C with LASSO algorithm in adult critically ill patients in surgical intensive care units: a bi-center prospective cohort study

利用LASSO算法预测外科重症监护病房成年危重患者的维生素C缺乏症:一项双中心前瞻性队列研究

Hu, Jie; Zhang, Jingwen; Li, Dawei; Hu, Xin; Li, Qi; Wang, Wenwen; Su, Jianguo; Wu, Di; Kang, Hongjun; Zhou, Feihu