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Predicting invasive ventilation and its effect on mortality for patients with pneumonia: an observational study using machine learning and a target trial approach

Predicting invasive ventilation and its effect on mortality for patients with pneumonia: an observational study using machine learning and a target trial approach
预测有创通气及其对肺炎患者死亡率的影响：使用机器学习和目标试验方法的观察性研究
批准号：
437164
负责人：
Yarnell Christopher J
金额：
$10.93万
依托单位：
University of Toronto
依托单位国家：
加拿大
项目类别：
Studentship Programs
财政年份：
2020
资助国家：
加拿大
项目状态：
已结题
起止时间：
2020-11-01 至 2023-11-01
来源：
https://webapps.cihr-irsc.gc.ca/decisions/p/project_details.html?applId=437164&lang=en
关键词：
Artifical Respiration Causal Inference Covid-19 Critical Care Medicine Critical Illness Intubation Machine Learning Mechanical Ventilation Pneumonia Target Trial

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中文摘要
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英文摘要
Pneumonia is a common, dangerous, and treatable cause of mortality and morbidity. More than 2 million people worldwide die from pneumonia each year, not including the accumulating mortality from the COVID-19 pandemic. The burden of pneumonia falls disprop
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Investigating invasive mechanical ventilation in patients with pneumonia and hypoxemic respiratory failure: which patients receive it, and which patients benefit?
  • 批准号：
    441136
  • 项目类别：
    Fellowship Programs
  • 资助金额：
    $12.02万
  • 财政年份：
    2020
  • 负责人：
    Yarnell Christopher J
  • 依托单位：
    University of Toronto
Advanced Trial Design in Critical Care Medicine
  • 批准号：
    406380
  • 项目类别：
    Studentship Programs
  • 资助金额：
    $1.27万
  • 财政年份：
    2018
  • 负责人：
    Yarnell Christopher J
  • 依托单位：
    University of Toronto
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