AIMC Topic: Pneumonia, Ventilator-Associated

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External validation and application of risk prediction model for ventilator-associated pneumonia in ICU patients with mechanical ventilation: A prospective cohort study.

International journal of medical informatics Apr 4, 2025
BACKGROUND: Early identification and prevention of ventilator-associated pneumonia (VAP) in patients with mechanical ventilation (MV) through reliable prediction model undergoing a rigorous and standardized process is essential for clinical decision-...
Female Risk Factors Aged Adult Humans Prospective Studies Intensive Care Units Respiration, Artificial China ROC Curve Pneumonia, Ventilator-Associated Male Middle Aged Risk Assessment
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Enhanced prediction of ventilator-associated pneumonia in patients with traumatic brain injury using advanced machine learning techniques.

Scientific reports Apr 2, 2025
Ventilator-associated pneumonia significantly increases morbidity, mortality, and healthcare costs among patients with traumatic brain injury. Accurately predicting risk can facilitate earlier interventions and improve patient outcomes. This study le...
Aged Adult Male Humans Brain Injuries, Traumatic Machine Learning Pneumonia, Ventilator-Associated Female Middle Aged Algorithms Risk Factors Support Vector Machine
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Machine learning prediction models for multidrug-resistant organism infections in ICU ventilator-associated pneumonia patients: Analysis using the MIMIC-IV database.

Computers in biology and medicine Mar 27, 2025
OBJECTIVE: This study aims to construct and compare four machine learning models using the MIMIC-IV database to identify high-risk factors for multidrug-resistant organism (MDRO) infection in Ventilator-associated pneumonia (VAP) patients.
Adult Male Middle Aged Drug Resistance, Multiple, Bacterial Female Risk Factors Aged Pneumonia, Ventilator-Associated Databases, Factual Intensive Care Units Humans Machine Learning
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Deep learning models for early and accurate diagnosis of ventilator-associated pneumonia in mechanically ventilated neonates.

Computers in biology and medicine Mar 3, 2025
BACKGROUND: Early and accurate confirmation of critically ill neonates with a suspected diagnosis of ventilator-associated pneumonia (VAP) can optimize the therapeutic strategy and avoid unnecessary use of empirical antibiotics. We aimed to examine w...
Infant, Newborn Male Respiration, Artificial Deep Learning Humans Female Pneumonia, Ventilator-Associated Intensive Care Units, Neonatal
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An interpretable machine learning model for predicting in-hospital mortality in ICU patients with ventilator-associated pneumonia.

PloS one Jan 7, 2025
BACKGROUND: Ventilator-associated pneumonia (VAP) is a common nosocomial infection in ICU, significantly associated with poor outcomes. However, there is currently a lack of reliable and interpretable tools for assessing the risk of in-hospital morta...
Hospital Mortality ROC Curve Pneumonia, Ventilator-Associated Aged Male Middle Aged Machine Learning Intensive Care Units Female Humans
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Machine learning models for the early prediction of ventilator-associated pneumonia: Author's reply.

European journal of internal medicine Mar 7, 2024
Pneumonia, Ventilator-Associated Humans Machine Learning
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Machine learning models for the early prediction of ventilator-associated pneumonia.

European journal of internal medicine Dec 30, 2023
Male Middle Aged Pneumonia, Ventilator-Associated Machine Learning Intensive Care Units Female Aged Humans
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Diagnosis of ventilator-associated pneumonia using electronic nose sensor array signals: solutions to improve the application of machine learning in respiratory research.

Respiratory research Feb 7, 2020
BACKGROUND: Ventilator-associated pneumonia (VAP) is a significant cause of mortality in the intensive care unit. Early diagnosis of VAP is important to provide appropriate treatment and reduce mortality. Developing a noninvasive and highly accurate ...
Electronic Nose Biomedical Research Female Respiratory Mechanics Case-Control Studies Male Humans Pneumonia, Ventilator-Associated Decision Trees Aged Middle Aged Machine Learning Intensive Care Units Aged, 80 and over
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Combined Use of Three Machine Learning Modeling Methods to Develop a Ten-Gene Signature for the Diagnosis of Ventilator-Associated Pneumonia.

Medical science monitor : international medical journal of experimental and clinical research Feb 7, 2020
BACKGROUND This study aimed to use three modeling methods, logistic regression analysis, random forest analysis, and fully-connected neural network analysis, to develop a diagnostic gene signature for the diagnosis of ventilator-associated pneumonia ...
Algorithms Gene Expression Profiling Protein Interaction Maps Databases, Genetic Humans Area Under Curve Molecular Sequence Annotation Pneumonia, Ventilator-Associated Machine Learning Gene Expression Regulation Gene Ontology Genome, Human
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Predicting ventilator-associated pneumonia with machine learning.

Medicine Jun 11, 2021
Ventilator-associated pneumonia (VAP) is the most common and fatal nosocomial infection in intensive care units (ICUs). Existing methods for identifying VAP display low accuracy, and their use may delay antimicrobial therapy. VAP diagnostics derived ...
Humans Aged Intensive Care Units Electronic Health Records Pneumonia, Ventilator-Associated Aged, 80 and over Middle Aged Sensitivity and Specificity Machine Learning Female Boston Adult Respiration, Artificial Forecasting Male Retrospective Studies
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