AIMC Topic: Intensive Care Units

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Machine learning models compared with current clinical indices to predict the outcome of high flow nasal cannula therapy in acute hypoxemic respiratory failure.

Critical care (London, England) Mar 7, 2025
BACKGROUND: Early identification of patients with acute hypoxemic respiratory failure (AHRF) who are at risk of failing high-flow nasal cannula (HFNC) therapy could facilitate closer monitoring, and timely adjustment/escalation of treatment. We aimed...
Female Aged Male Middle Aged Brazil Humans Machine Learning Intensive Care Units Cannula ROC Curve Respiratory Insufficiency Hypoxia Oxygen Inhalation Therapy
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Leveraging Artificial Intelligence to Reduce Neuroscience ICU Length of Stay.

Journal of healthcare management / American College of Healthcare Executives Mar 6, 2025
GOAL: Efficient patient flow is critical at Tampa General Hospital (TGH), a large academic tertiary care center and safety net hospital with more than 50,000 discharges and 30,000 surgical procedures per year. TGH collaborated with GE HealthCare Comm...
Artificial Intelligence Intensive Care Units Length of Stay Efficiency, Organizational Humans Neurosciences
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Machine Learning-Based Prediction of Delirium and Risk Factor Identification in Intensive Care Unit Patients With Burns: Retrospective Observational Study.

JMIR formative research Mar 5, 2025
BACKGROUND: The incidence of delirium in patients with burns receiving treatment in the intensive care unit (ICU) is high, reaching up to 77%, and has been associated with increased mortality rates. Therefore, early identification of patients at high...
Machine Learning Retrospective Studies Intensive Care Units Female Humans Middle Aged Risk Assessment ROC Curve Burns Delirium Risk Factors Aged Adult Male
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Explainable machine learning model for predicting acute pancreatitis mortality in the intensive care unit.

BMC gastroenterology Mar 3, 2025
BACKGROUND: Current prediction models are suboptimal for determining mortality risk in patients with acute pancreatitis (AP); this might be improved by using a machine learning (ML) model. In this study, we aimed to construct an explainable ML model ...
Acute Disease APACHE Pancreatitis Female Aged Adult Male Middle Aged Risk Assessment Humans Machine Learning Intensive Care Units Severity of Illness Index Hospital Mortality ROC Curve
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Interpretable machine learning model for early morbidity risk prediction in patients with sepsis-induced coagulopathy: a multi-center study.

Frontiers in immunology Mar 3, 2025
BACKGROUND: Sepsis-induced coagulopathy (SIC) is a complex condition characterized by systemic inflammation and coagulopathy. This study aimed to develop and validate a machine learning (ML) model to predict SIC risk in patients with sepsis.
Middle Aged Female Blood Coagulation Disorders Humans Risk Assessment Risk Factors Machine Learning Sepsis Aged Retrospective Studies ROC Curve Male Intensive Care Units
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Relationship between atherogenic index of plasma and length of stay in critically ill patients with atherosclerotic cardiovascular disease: a retrospective cohort study and predictive modeling based on machine learning.

Cardiovascular diabetology Feb 28, 2025
BACKGROUND: The atherogenic index of plasma (AIP) is considered an important marker of atherosclerosis and cardiovascular risk. However, its potential role in predicting length of stay (LOS), especially in patients with atherosclerotic cardiovascular...
Triglycerides Critical Illness Intensive Care Units Humans Female Risk Factors Machine Learning Aged Length of Stay Databases, Factual Decision Support Techniques Male Time Factors Predictive Value of Tests Biomarkers Middle Aged Prognosis Atherosclerosis Risk Assessment Retrospective Studies Cholesterol, HDL
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Machine Learning-Based Mortality Prediction for Acute Gastrointestinal Bleeding Patients Admitted to Intensive Care Unit.

Current medical science Feb 27, 2025
OBJECTIVE: The study aimed to develop machine learning (ML) models to predict the mortality of patients with acute gastrointestinal bleeding (AGIB) in the intensive care unit (ICU) and compared their prognostic performance with that of Acute Physiolo...
Male Middle Aged Hospital Mortality ROC Curve Area Under Curve Acute Disease APACHE Gastrointestinal Hemorrhage Prognosis Intensive Care Units Female Aged Humans Machine Learning Algorithms
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Prioritisation of functional needs for ICU intelligent robots in China: a consensus study based on the national survey and nominal group technique.

BMJ open Feb 26, 2025
OBJECTIVE: This study aims to define the prioritisation of the needs for an intelligent robot's functions in the intensive care unit (ICU) from a clinical perspective.
Critical Care Autonomous Robots Surveys and Questionnaires Humans Delphi Technique Consensus Intensive Care Units Robotics Male China
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Predicting the risk of acute kidney injury in patients with acute pancreatitis complicated by sepsis using a stacked ensemble machine learning model: a retrospective study based on the MIMIC database.

BMJ open Feb 26, 2025
OBJECTIVE: This study developed and validated a stacked ensemble machine learning model to predict the risk of acute kidney injury in patients with acute pancreatitis complicated by sepsis.
ROC Curve Pancreatitis Male Middle Aged Risk Assessment Sepsis Female Risk Factors Aged Adult Humans Machine Learning Algorithms Retrospective Studies Databases, Factual Acute Kidney Injury Intensive Care Units
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Predicting Agitation-Sedation Levels in Intensive Care Unit Patients: Development of an Ensemble Model.

JMIR medical informatics Feb 26, 2025
BACKGROUND: Agitation and sedation management is critical in intensive care as it affects patient safety. Traditional nursing assessments suffer from low frequency and subjectivity. Automating these assessments can boost intensive care unit (ICU) eff...
Middle Aged Hypnotics and Sedatives Psychomotor Agitation Humans Machine Learning Intensive Care Units Female Aged Male
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