AIMC Topic: Intensive Care Units
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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.
Constructing an early warning model for elderly sepsis patients based on machine learning.
Scientific reports
Mar 27, 2025
Sepsis is a serious threat to human life. Early prediction of high-risk populations for sepsis is necessary especially in elderly patients. Artificial intelligence shows benefits in early warning. The aim of the study was to construct an early machin...
Multicenter Development and Prospective Validation of eCARTv5: A Gradient-Boosted Machine-Learning Early Warning Score.
Critical care explorations
Mar 26, 2025
BACKGROUND: Early detection of clinical deterioration using machine-learning early warning scores may improve outcomes. However, most implemented scores were developed using logistic regression, only underwent retrospective validation, and were not t...
Point-of-Care Sensors and Medical Internet-of-Things Technologies to Manage Catheter-Associated Urinary Tract Infections in the Intensive Care Unit.
Critical care nursing clinics of North America
Mar 24, 2025
This article examines the current technologies used with indwelling urinary catheters to monitor potential catheter-associated urinary tract infections (CAUTIs) in the intensive care unit. Advancements in medical internet-of-things, artificial intell...
The future of artificial intelligence in cardiovascular monitoring.
Current opinion in critical care
Mar 24, 2025
PURPOSE OF REVIEW: Cardiovascular monitoring is essential for managing hemodynamic instability and preventing complications in critically ill patients. Conventional monitoring approaches are limited by predefined thresholds, dependence on clinician e...
Eye movement detection using electrooculography and machine learning in cardiac arrest patients.
Resuscitation
Mar 24, 2025
AIM: To train a machine learning algorithm to identify eye movement from electrooculography (EOG) in cardiac arrest (CA) patients. Neuroprognostication of comatose post-CA patients is challenging, requiring novel biomarkers to guide decision making. ...
Explainable SHAP-XGBoost models for pressure injuries among patients requiring with mechanical ventilation in intensive care unit.
Scientific reports
Mar 22, 2025
pressure injuries are significant concern for ICU patients on mechanical ventilation. Early prediction is crucial for enhancing patient outcomes and reducing healthcare costs. This study aims to develop a predictive model using machine learning techn...
Enhanced machine learning predictive modeling for delirium in elderly ICU patients with COPD and respiratory failure: A retrospective study based on MIMIC-IV.
PloS one
Mar 20, 2025
BACKGROUND AND OBJECTIVE: Elderly patients with Chronic obstructive pulmonary disease (COPD) and respiratory failure admitted to the intensive care unit (ICU) have a poor prognosis, and the occurrence of delirium further worsens outcomes and increase...
Development and validation of machine learning-based prediction model for outcome of cardiac arrest in intensive care units.
Scientific reports
Mar 13, 2025
Cardiac arrest (CA) poses a significant global health challenge and often results in poor prognosis. We developed an interpretable and applicable machine learning (ML) model for predicting in-hospital mortality of CA patients who survived more than 7...
Development and validation of an interpretable machine learning model for predicting in-hospital mortality for ischemic stroke patients in ICU.
International journal of medical informatics
Mar 9, 2025
BACKGROUND: Timely and accurate outcome prediction is essential for clinical decision-making for ischemic stroke patients in the intensive care unit (ICU). However, the interpretation and translation of predictive models into clinical applications ar...
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