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Tamás Szakmány

Cleveland Clinic Foundation
H指数:47
被引数:1.0万

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Bedside identification of subphenotypes in acute respiratory failure (PHIND): a multicentre, observational cohort study

急性呼吸衰竭 (PHIND) 亚表型的床旁鉴定: 一项多中心,观察性队列研究

2026-03-230
OAAI
Predicting Outcome and Duration of Mechanical Ventilation in Acute Hypoxemic Respiratory Failure: The PREMIER Study

预测急性低氧性呼吸衰竭患者机械通气的结局和持续时间:PREMIER研究

2025-11-070
OAAI
Procalcitonin evaluation of antibiotic use in COVID-19 hospitalised patients: The PEACH mixed methods study

降钙素原对新型冠状病毒肺炎住院患者抗生素使用的评估: 桃子混合方法研究

2025-11-010
PRE
Early Prediction of ICU Mortality in Patients with Acute Hypoxemic Respiratory Failure Using Machine Learning: The MEMORIAL Study

使用机器学习早期预测急性低氧性呼吸衰竭患者的ICU死亡率: 纪念研究

2025-03-010
OAAI
Prone positioning is associated with increased insulin requirements in mechanically ventilated patients with COVID-19

俯卧位与新型冠状病毒肺炎机械通气患者胰岛素需求增加有关

2024-11-120
OAAI
A retrospective propensity-score-matched cohort study of the impact of procalcitonin testing on antibiotic use in hospitalized patients during the first wave of COVID-19

第一波新型冠状病毒肺炎期间降钙素原检测对住院患者抗生素使用影响的回顾性倾向评分匹配队列研究

2024-09-090
OAAI
The cost-effectiveness of procalcitonin for guiding antibiotic prescribing in individuals hospitalized with COVID-19: part of the PEACH study

降钙素原指导新型冠状病毒肺炎住院患者抗生素处方的成本效益: PEACH研究的一部分

2024-06-061
OAAI
Predicting the Length of Mechanical Ventilation in Acute Respiratory Disease Syndrome Using Machine Learning: The PIONEER Study

使用机器学习预测急性呼吸道疾病综合征的机械通气时间: 先锋研究

2024-03-210
OAAI
Patient diversity and author representation in clinical studies supporting the Surviving Sepsis Campaign guidelines for management of sepsis and septic shock 2021: a systematic review of citations
2023-11-016
OAAI
Predicting ICU Mortality in Acute Respiratory Distress Syndrome Patients Using Machine Learning: The Predicting Outcome and STratifiCation of severity in ARDS (POSTCARDS) Study
2023-08-316
PRE