AI Medical Compendium Topic:
Intensive Care Units

Clear Filters Showing 491 to 500 of 607 articles

The effect of robotic telerounding in the surgical intensive care units impact on medical education.

Journal of robotic surgery Oct 8, 2014
Robotic telerounding is effective from the standpoint of patients' satisfaction and patients' care in teaching and community hospitals. However, the impact of robotic telerounding by the intensivist rounding remotely in the surgical intensive care un...
Education, Medical Teaching Rounds Surveys and Questionnaires Humans Treatment Outcome Intensive Care Units Robotics Students, Medical
View on PubMed DOI

Rapid Response System Restructure: Focus on Prevention and Early Intervention.

Critical care nursing quarterly May 13, 2025
This article describes the staged restructure of the rapid response program into a dedicated 24/7 proactive rapid response system in a quaternary academic medical center in the southern United States. Rapid response nurses (RRNs) completed clinical l...
Inpatients Humans Heart Arrest Hospital Mortality Artificial Intelligence United States Intensive Care Units
View on PubMed DOI

Fast and interpretable mortality risk scores for critical care patients.

Journal of the American Medical Informatics Association : JAMIA Apr 1, 2025
OBJECTIVE: Prediction of mortality in intensive care unit (ICU) patients typically relies on black box models (that are unacceptable for use in hospitals) or hand-tuned interpretable models (that might lead to the loss in performance). We aim to brid...
Humans Intensive Care Units Machine Learning Risk Assessment Algorithms Hospital Mortality Critical Illness Critical Care
View on PubMed DOI

[Establishing of mortality predictive model for elderly critically ill patients using simple bedside indicators and interpretable machine learning algorithms].

Zhonghua wei zhong bing ji jiu yi xue Feb 1, 2025
OBJECTIVE: To explore the feasibility of incorporating simple bedside indicators into death predictive model for elderly critically ill patients based on interpretability machine learning algorithms, providing a new scheme for clinical disease assess...
Humans Machine Learning Critical Illness Intensive Care Units Female Aged Algorithms Prognosis Retrospective Studies Organ Dysfunction Scores Male Hospital Mortality APACHE
View on PubMed DOI

Scale to predict risk for refractory septic shock based on a hybrid approach using machine learning and regression modeling.

Emergencias : revista de la Sociedad Espanola de Medicina de Emergencias Feb 1, 2025
OBJECTIVE: To develop a scale to predict refractory septic shock (SS) based on clinical variables recorded during initial evaluations of patients.
Emergency Service, Hospital Registries Norepinephrine ROC Curve Shock, Septic Regression Analysis Retrospective Studies Intensive Care Units Female Middle Aged Humans Aged Risk Assessment Machine Learning Male
View on PubMed DOI

[Predicting Intensive Care Unit Mortality in Patients With Heart Failure Combined With Acute Kidney Injury Using an Interpretable Machine Learning Model: A Retrospective Cohort Study].

Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition Jan 20, 2025
OBJECTIVE: Heart failure (HF) complicated by acute kidney injury (AKI) significantly impacts patient outcomes, and it is crucial to make early predictions of short-term mortality. This study is focused on developing an interpretable machine learning ...
Hospital Mortality Heart Failure Retrospective Studies Acute Kidney Injury Intensive Care Units Humans Male Machine Learning Female Prognosis Middle Aged Aged
View on PubMed DOI

Individualized multi-treatment response curves estimation using RBF-net with shared neurons.

Biometrics Jan 7, 2025
Heterogeneous treatment effect estimation is an important problem in precision medicine. Specific interests lie in identifying the differential effect of different treatments based on some external covariates. We propose a novel non-parametric treatm...
Biometry Statistics, Nonparametric Markov Chains Organ Dysfunction Scores Monte Carlo Method Precision Medicine Intensive Care Units Length of Stay Models, Statistical Bayes Theorem Sepsis Treatment Outcome Neural Networks, Computer Algorithms Computer Simulation Humans
View on PubMed DOI

Explainable Artificial Intelligence for Early Prediction of Pressure Injury Risk.

American journal of critical care : an official publication, American Association of Critical-Care Nurses Sep 1, 2024
BACKGROUND: Hospital-acquired pressure injuries (HAPIs) have a major impact on patient outcomes in intensive care units (ICUs). Effective prevention relies on early and accurate risk assessment. Traditional risk-assessment tools, such as the Braden S...
ROC Curve Pressure Ulcer Male Middle Aged Risk Assessment Female Risk Factors Aged Artificial Intelligence Machine Learning Humans Algorithms Intensive Care Units
View on PubMed DOI

Optimize individualized energy delivery for septic patients using predictive deep learning models.

Asia Pacific journal of clinical nutrition Sep 1, 2024
BACKGROUND AND OBJECTIVES: We aim to establish deep learning models to optimize the individualized energy delivery for septic patients.
Humans Aged Male Intensive Care Units Female Sepsis Middle Aged Energy Intake Deep Learning
View on PubMed DOI

Optimizing ICU Care: Machine Learning and PCA for Early Prediction of Renal Replacement Therapy Requirement.

Studies in health technology and informatics Aug 22, 2024
Forecasting the need for Renal Replacement Therapy (RRT) in intensive care units (ICUs) at an early stage can enhance patient outcomes and optimize resource allocation. The study aimed to develop a model for early prediction of Renal Replacement Ther...
Machine Learning Renal Replacement Therapy Intensive Care Units Male Humans Principal Component Analysis Critical Care
View on PubMed DOI
Popular Topics
Recent Journals