AIMC Topic: Intensive Care Units
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Machine learning prediction of unexpected readmission or death after discharge from intensive care: A retrospective cohort study.
Journal of clinical anesthesia
Oct 14, 2024
BACKGROUND: Intensive care units (ICUs) harbor the sickest patients with the utmost needs of medical care. Discharge from ICU needs to consider the reason for admission and stability after ICU care. Organ dysfunction or instability after ICU discharg...
Comparing ensemble learning algorithms and severity of illness scoring systems in cardiac intensive care units: a retrospective study.
Einstein (Sao Paulo, Brazil)
Oct 14, 2024
BACKGROUND: Beatriz Nistal-Nuño designed a machine learning system type of ensemble learning for patients undergoing cardiac surgery and intensive care unit cardiology patients, based on sequences of cardiovascular physiological measurements and othe...
Is artificial intelligence prepared for the 24-h shifts in the ICU?
Anaesthesia, critical care & pain medicine
Oct 3, 2024
Integrating machine learning (ML) into intensive care units (ICUs) can significantly enhance patient care and operational efficiency. ML algorithms can analyze vast amounts of data from electronic health records, physiological monitoring systems, and...
Prognosis of major bleeding based on residual variables and machine learning for critical patients with upper gastrointestinal bleeding: A multicenter study.
Journal of critical care
Oct 2, 2024
BACKGROUND: Upper gastrointestinal bleeding (UGIB) is a significant cause of morbidity and mortality worldwide. This study investigates the use of residual variables and machine learning (ML) models for predicting major bleeding in patients with seve...
Development and validation of a sepsis risk index supporting early identification of ICU-acquired sepsis: an observational study.
Anaesthesia, critical care & pain medicine
Oct 2, 2024
BACKGROUND: Sepsis is a threat to global health, and domestically is the major cause of in-hospital mortality. Due to increases in inpatient morbidity and mortality resulting from sepsis, healthcare providers (HCPs) would accrue significant benefits ...
Explainable machine learning and online calculators to predict heart failure mortality in intensive care units.
ESC heart failure
Sep 19, 2024
AIMS: This study aims to develop explainable machine learning models and clinical tools for predicting mortality in patients in the intensive care unit (ICU) with heart failure (HF).
Early Prediction of Cardiac Arrest in the Intensive Care Unit Using Explainable Machine Learning: Retrospective Study.
Journal of medical Internet research
Sep 17, 2024
BACKGROUND: Cardiac arrest (CA) is one of the leading causes of death among patients in the intensive care unit (ICU). Although many CA prediction models with high sensitivity have been developed to anticipate CA, their practical application has been...
Criticality of Nursing Care for Patients With Alzheimer's Disease in the ICU: Insights From MIMIC III Dataset.
Clinical nursing research
Sep 16, 2024
Alzheimer's disease (AD) patients admitted to intensive care units (ICUs) exhibit varying survival outcomes due to the unique challenges in managing AD patients. Stratifying patient mortality risk and understanding the criticality of nursing care are...
Predicting hypoglycemia in ICU patients: a machine learning approach.
Expert review of endocrinology & metabolism
Sep 16, 2024
BACKGROUND: The current study sets out to develop and validate a robust machine-learning model utilizing electronic health records (EHR) to forecast the risk of hypoglycemia among ICU patients in Jordan.
Development and evaluation of a model for predicting the risk of healthcare-associated infections in patients admitted to intensive care units.
Frontiers in public health
Sep 12, 2024
This retrospective study used 10 machine learning algorithms to predict the risk of healthcare-associated infections (HAIs) in patients admitted to intensive care units (ICUs). A total of 2,517 patients treated in the ICU of a tertiary hospital in Ch...
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