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Community-acquired pneumonia: Machine learning enhances early risk prediction in hospitalized patients

Community-acquired pneumonia: Machine learning enhances early risk prediction in hospitalized patients
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Machine-learning model superior in community-acquired pneumonia mortality prediction

A machine-learning model showed excellent discriminative ability in predicting 30-day mortality in patients with community-acquired pneumonia, according to study results published in CHEST.“[SepsisFinder adapted for CAP with machine learning] offers some advantages over current scoring methods, for example, calculations easily made on routinely collected data and based on structured

New Machine Learning Tool to Predict Pneumonia Progression Outperforms PSI

A newly developed machine learning model to predict clinical deterioration in pneumonia outperformed the pneumonia severity index.

Common scoring systems comparably predict mortality in SARS-CoV-2-related CAP

Two widely used clinical scoring systems — the Pneumonia Severity Index and CURB-65 score — comparatively predicted in-hospital mortality in patients with and without SARS-CoV-2-related community-acquired pneumonia, researchers reported.“Triaging patients with SARS-CoV-2 community-acquired pneumonia requires an accurate assessment of mortality risk; however, this is challenging

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