Critical Care

Development and internal validation of machine learning in predicting prognosis of acute kidney injury patients in resource-limited setting.

BACKGROUND: Machine learning models for predicting acute kidney injury (AKI) prognosis have primaril...

Application of machine learning for the diagnosis and prognosis of sepsis-induced acute respiratory distress syndrome: a systematic review and meta-analysis.

A cascaded CNN-LSTM framework for quantifying respiratory motion from surface electromyographic signals.

OBJECTIVE: Surface electromyographic (sEMG) signals of the diaphragm provide a valuable physiologica...

A hybrid learning framework for automated multiclass electrocardiogram classification with SimCardioNet.

Electrocardiography is a cornerstone in the diagnosis of cardiovascular diseases; however, accurate ...

Flow-driven left ventricular remodelling in long-term haemodialysis: a multicenter model of arteriovenous access-induced cardiac load.

BACKGROUND: Arteriovenous (AV) access, an essential component of dialysis treatment, has been implic...

When distress meets technology: The mediating role of AI integration in the link between nurses' moral distress and moral integrity in critical care settings.

BACKGROUND: Moral distress is increasingly recognized as a critical challenge in critical care setti...

Using human-robot interaction to assess emotion recognition in dialysis patients: A preliminary study.

This cross-sectional observational study examined the relationship between psychological factors and...

The effect of artificial intelligence-assisted pulmonary rehabilitation on exercise capacity: A systematic review and meta-analysis.

INTRODUCTION: Artificial intelligence (AI) technologies are increasingly being integrated into pulmo...

Synergistic impact of Gram-negative bacterial co-infection on invasive pulmonary aspergillosis in non-neutropenic patients: a machine learning-based risk stratification approach.

BACKGROUND: Invasive pulmonary aspergillosis (IPA) is increasingly recognized in non-neutropenic pat...

A randomized controlled trial of artificial intelligence-based analytics for clinical deterioration.

This pragmatic randomized controlled trial aimed to assess the effect of a passive display of artifi...

Explainable machine learning-based 28-day mortality prediction model for elderly patients with acute kidney injury.

Elderly patients with acute kidney injury (AKI) face a significantly increased mortality risk. Recen...

Evaluation of oxygenation indices incorporating SpO₂ and PEEP for assessing ARDS severity: Evidence from the MIMIC-IV and eICU collaborative research database v2.0 databases.

BACKGROUND: The in-hospital mortality of acute respiratory distress syndrome can reach 35-45%, with ...

Iatrogenic plasticizer Di(2-ethylhexyl) phthalate (DEHP) exposure increases Sepsis mortality risk: Machine learning implicates monocyte-driven immune dysregulation.

Sepsis poses a significant global health burden, and ICU patients are disproportionately exposed to ...

Impacts of delayed influenza vaccination on clinical outcomes in ICU-admitted patients with influenza: A retrospective cohort study.

BACKGROUND: Influenza vaccination is an effective measure for reducing the risk of severe influenza ...

A scoping review of portable ultra-low-field MRI studies in patients with acquired brain injury: Past, present, and future.

Acquired Brain Injury (ABI) refers to any post-birth damage to the brain, commonly resulting from tr...

Explainable machine learning model for predicting short-term outcomes in sepsis- induced coagulopathy.

BACKGROUND: Sepsis-Induced coagulopathy (SIC) is not only a common complication in the development p...

Association of lactate-to-albumin ratio with 28-day mortality in elderly sepsis patients: a retrospective MIMIC-IV database analysis.

BACKGROUND: The lactate-to-albumin ratio (LAR) is correlated with mortality in critically ill patien...

Construction of a depression risk prediction model for hepatitis B patients based on machine learning strategy.

BACKGROUND: Hepatitis B (HBV) is a chronic viral infection that can lead to cirrhosis, liver failure...

Early heart-rate trajectory phenotypes predict short-term mortality in critically ill patients: a dynamic time-warping cluster analysis.

UNLABELLED: Heart rate (HR) reflects illness severity in critically ill patients, but the prognostic...

Development and Validation of a Machine Learning Model That Uses Voice to Predict Aspiration Risk.

BACKGROUND: Aspiration causes or aggravates a variety of respiratory diseases. Subjective bedside ev...

K-MIMIC: a nationwide Korean multi-institutional Multimodal intensive care dataset.

BACKGROUND: Recent advancements in critical care have highlighted the need for comprehensive, multim...