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A Machine Learning Method for Early Stewardship of Invasive Mechanical Ventilation in Patients with Sepsis

2024-02-22

Abstract excerpt

<h4>Background: </h4> Heterogeneity among mechanically ventilated patients with sepsis makes it challenging to define appropriate treatments. This study aimed to establish a method for identifying high-risk patients in this vulnerable population. To this end, unsupervised machine learning models were used to analyze a large volume of real-world clinical data for determining prognosis in these patients at an early...

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Literature Corpus work
46127959-f0ca-51fd-9784-dfa2120acabd
DOI
10.21203/rs.3.rs-3970283/v1
Open publication

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A Machine Learning Method for Early Stewardship of Invasive Mechanical Ventilation in Patients with SepsisDOI 10.21203/rs.3.rs-3970283/v1
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