AIMC Topic: Intensive Care Units
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Beyond labels: determining the true type of blood gas samples in ICU patients through supervised machine learning.
BMC medical informatics and decision making
Jul 24, 2025
BACKGROUND: In the Intensive Care Unit (ICU), data stored in patient data management systems (PDMS) is commonly used in clinical practice and research. Parameters from point-of-care arterial blood gas (BG) analysis are used in the diagnosis and defin...
Predicting In-Hospital Mortality in Intensive Care Unit Patients Using Causal SurvivalNet With Serum Chloride and Other Causal Factors: Cross-Country Study.
Journal of medical Internet research
Jul 24, 2025
BACKGROUND: Incorporating initial serum chloride levels as a prognostic indicator in the intensive care environment has the potential to refine risk stratification and tailor treatment strategies, leading to more efficient use of clinical resources a...
Early detection of ICU-acquired infections using high-frequency electronic health record data.
BMC medical informatics and decision making
Jul 21, 2025
BACKGROUND: Nosocomial infections are a major cause of morbidity and mortality in the ICU. Earlier identification of these complications may facilitate better clinical management and improve outcomes. We developed a dynamic prediction model that leve...
Analysis of aPTT predictors after unfractionated heparin administration in intensive care units using machine learning models.
PloS one
Jul 21, 2025
OBJECTIVES: Predicting optimal coagulation control using heparin in intensive care units (ICUs) remains a significant challenge. This study aimed to develop a machine learning (ML) model to predict activated partial thromboplastin time (aPTT) in ICU ...
Development and temporal validation of a nomogram for predicting ICU 28-day mortality in middle-aged and elderly sepsis patients: An eICU database study.
PloS one
Jul 21, 2025
BACKGROUND AND OBJECTIVE: Despite advances in intensive care, sepsis remains a leading cause of mortality in intensive care unit (ICU) patients, especially middle-aged and elderly individuals. Given the limitations of conventional scoring systems and...
Machine learning for the prediction of augmented renal clearance (ARC) in patients with sepsis in critical care units.
Scientific reports
Jul 18, 2025
This study aims to establish and validate prediction models based on novel machine learning (ML) algorithms for augmented renal clearance (ARC) in critically ill patients with sepsis. Patients with sepsis were extracted from the Medical Information M...
AI-powered skin spectral imaging enables instant sepsis diagnosis and outcome prediction in critically ill patients.
Science advances
Jul 18, 2025
With sepsis remaining a leading cause of mortality, early identification of patients with sepsis and those at high risk of death is a challenge of high socioeconomic importance. Given the potential of hyperspectral imaging (HSI) to monitor microcircu...
Development of a machine learning-derived model to predict unplanned ICU admissions after major non-cardiac surgery.
BMC anesthesiology
Jul 17, 2025
BACKGROUND: Unplanned postoperative intensive care unit admissions (UIAs) are rare events that cause significant challenges to perioperative workflow. We describe the development of a machine-learning derived model to predict UIAs using only widely u...
Effectiveness of predictive scoring systems in predicting mortality in relation to baseline kidney function in adult intensive care unit patients: a systematic review protocol.
BMJ open
Jul 17, 2025
INTRODUCTION: Predictive scoring systems support clinicians in decision-making by estimating the prognosis of patients in intensive care units (ICUs). However, there is limited evidence on the accuracy of these systems in predicting mortality and org...
Development of a risk prediction model for sepsis-related delirium based on multiple machine learning approaches and an online calculator.
PloS one
Jul 16, 2025
BACKGROUND: Sepsis-associated delirium (SAD) occurs due to disruptions in neurotransmission linked to inflammatory responses from infections. It poses significant challenges in clinical management and is associated with poor outcomes. Survivors often...
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