AIMC Topic: Intensive Care Units

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CRISP: A causal relationships-guided deep learning framework for advanced ICU mortality prediction.

BMC medical informatics and decision making
BACKGROUND: Mortality prediction is critical in clinical care, particularly in intensive care units (ICUs), where early identification of high-risk patients can inform treatment decisions. While deep learning (DL) models have demonstrated significant...

Unraveling relevant cross-waves pattern drifts in patient-hospital risk factors among hospitalized COVID-19 patients using explainable machine learning methods.

BMC infectious diseases
BACKGROUND: Several studies explored factors related to adverse clinical outcomes among COVID-19 patients but lacked analysis of the impact of the temporal data shifts on the strength of association between different predictors and adverse outcomes. ...

Clinical subtypes identification and feature recognition of sepsis leukocyte trajectories based on machine learning.

Scientific reports
Sepsis is a highly variable condition, and tracking leukocyte patterns may offer insights for tailored treatment and prognosis. We used the MIMIC-IV database to analyze patients diagnosed with Sepsis-3 within 24 h of ICU admission. Latent class mixed...

Comprehensive analyses: Using machine learning models for mortality prediction in the intensive care unit of internal medicine.

Journal of investigative medicine : the official publication of the American Federation for Clinical Research
Mortality prediction in the intensive care unit (ICU) is essential in patient management. Emerging methods such as machine learning (ML) can be employed to predict ICU patients' mortality. Patients receiving treatment in the ICU of the internal medic...

Revolutionizing Intensive Care Unit Care: A Scoping Review of Multimodal Family Engagement Technologies.

Critical care nursing clinics of North America
This scoping review systematically examines the emerging field of multimodal family engagement technologies in intensive care units (ICUs). Despite significant advancements in medical technology, family engagement remains an underutilized resource in...

Predicting hospital admissions, ICU utilization, and prolonged length of stay among febrile pediatric emergency department patients using incomplete and imbalanced electronic health record (EHR) data strategies.

International journal of medical informatics
OBJECTIVE: Determine the efficacy of commonly used approaches to handling missing and/or imbalanced Electronic Health Record (EHR) data on the performance of predictive models targeting risk of admission, intensive care unit (ICU) use, or prolonged l...

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
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-...

Real-time surveillance system for patient deterioration: a pragmatic cluster-randomized controlled trial.

Nature medicine
The COmmunicating Narrative Concerns Entered by RNs (CONCERN) early warning system (EWS) uses real-time nursing surveillance documentation patterns in its machine learning algorithm to identify deterioration risk. We conducted a 1-year, multisite, pr...

Development and Validation of a Machine Learning Model for Early Prediction of Delirium in Intensive Care Units Using Continuous Physiological Data: Retrospective Study.

Journal of medical Internet research
BACKGROUND: Delirium in intensive care unit (ICU) patients poses a significant challenge, affecting patient outcomes and health care efficiency. Developing an accurate, real-time prediction model for delirium represents an advancement in critical car...

Machine Learning-Guided Fluid Resuscitation for Acute Pancreatitis Improves Outcomes.

Clinical and translational gastroenterology
INTRODUCTION: Ariel Dynamic Acute Pancreatitis Tracker (ADAPT) is an artificial intelligence tool using mathematical algorithms to predict severity and manage fluid resuscitation needs based on the physiologic parameters of individual patients. Our a...