Critical Care

Optimal machine learning models and factors for global infectious diseases: An ecological analysis.

BACKGROUND: Infectious diseases are a major global public health challenge. Socioeconomic and enviro...

Proteomic profiling and pathway analyses reveal molecular signatures and immune networks in pediatric sepsis.

BACKGROUND: Sepsis remains a leading cause of childhood mortality worldwide. Most deaths occur withi...

Combined use of serum KL-6 and respiratory functional parameters for identifying fibrotic lung damage in SARS-CoV-2-induced interstitial pneumonia.

BACKGROUND: Post-COVID19 pulmonary fibrosis (PCPF) has been reported in a significant proportion of ...

AI-derived left-to-right cardiac chamber volume ratios in coronary artery calcium scans strongly predict heart failure.

AIMS: The AI-CVD initiative seeks to extract actionable insights from coronary artery calcium (CAC) ...

At the Edge of Chaos: Complexity Science and Critical Care in the Era of Artificial Intelligence.

Critical care unfolds at the crossroads of highly complex, nonlinear systems. The intersection of pa...

Machine learning predicts sepsis deterioration trajectories.

Sepsis has heterogeneous clinical trajectories, but conventional severity scores offer only static r...

Characterizing heterogeneity and subphenotyping acute respiratory distress syndrome with computed tomography.

Acute respiratory distress syndrome (ARDS) is a heterogeneous clinical syndrome rather than a single...

Subtypes estimation in single-cell multi-omics data via S-multi-SNE.

Single-cell RNA sequencing (scRNA-seq) has rapidly become an essential method in modern biology, as ...

Nonlinear dynamical analysis of chaos, fractal complexity, and entropy in EEG signals during music therapy in ICU burn patients.

Music therapy (MT) is known to influence brain dynamics; however, its effects on nonlinear electroen...

A Multi-Scale Hybrid Efficient Deep Learning Model for COPD Detection Using Respiratory Sounds.

Chronic obstructive pulmonary disease (COPD) is a prevalent respiratory disease, and early diagnosis...

International Delphi consensus on acute kidney injury: Foundations for AI-driven digital twin development in critical care nephrology.

BACKGROUND: Acute kidney injury (AKI) in critically ill patients is clinically complex and heterogen...

A cost-sensitive multiclass machine learning framework for postoperative neurosurgical triage (Neuro-TACTIC).

Postoperative placement of patients into a regular ward, an intermediate-care unit (IMC), or an inte...

Letter to the Editor: "Evaluating the efficacy of large language models in predicting intensive care unit admission needs".

This letter comments on the study by Turan et al., which evaluates the efficacy of large language mo...

The Impact of Evaluation Strategy on Sepsis Prediction Model Performance Metrics in Intensive Care Data: Retrospective Cohort Study.

BACKGROUND: The prediction of the onset of sepsis, a life-threatening condition resulting from a dys...

Extubation Decision Support in Critical Care: A Multimodal Machine Learning Framework Integrating Segmented Radiographs and Routine Clinical Data.

Extubation failure remains a major challenge in critically ill patients and is associated with adver...

How ICU clinicians document 'Futility': A 10-year analysis of critical care notes using natural language processing notes.

BACKGROUND: ICU patients frequently receive treatments clinicians perceive are futile which can caus...

Combined variations in sleep, physical activity, and nutrition and the risk of major adverse cardiovascular events.

AIMS: Sleep, physical activity, and nutrition (SPAN) are major lifestyle behaviours that influence c...

Longitudinal Subphenotyping of Acute Respiratory Distress Syndrome: Implications in Prognostic Prediction and Clinical Intervention.

BACKGROUND AND OBJECTIVE: To identify the longitudinal subphenotypes (LSPs) in patients with acute r...

Letter to the Editor: Nocturnal enteral feeding and mechanical ventilation risk in intensive care unit patients: A deep Learning-Based causal inference study.

Targeting autophagy in Duchenne muscular dystrophy: mechanistic insights and emerging therapeutic strategies.

Duchenne muscular dystrophy (DMD) is a severe X-linked myopathy characterised by progressive skeleta...

Identification and experimental validation of biomarkers associated with integrated stress response in sepsis.

BACKGROUND: Strategies that specifically target the integrated stress response (ISR) as a therapeuti...