Intensivists

Infrared thermography in the detection of arthritis: a systematic review of diagnostic performance compared with joint ultrasound.

Early detection of arthritis in autoimmune rheumatic diseases (ARDs) is critical to prevent irrevers...

[Annual progress in critical care of pulmonary medicine 2025].

This review systematically summarizes the annual research advances in the field of critical care of ...

Modern machine learning techniques used in prediction of sepsis and bloodstream infection in burn patients: A systematic review.

INTRODUCTION: Burn patients are a group highly prone to sepsis and bloodstream infections (BSIs) due...

Community medical centers struggle to produce well-calibrated clinical prediction models: Data augmentation can help.

OBJECTIVE: Machine learning models (ML) often require localization to perform optimally in local pop...

A machine learning-based model to predict multi-time-point prognosis for acute-on-chronic hepatitis B liver failure.

Our prognostic model and mobile application enable multi-time-point prognostic evaluation for patien...

Identifying and timing patient outcomes in clinician notes using large language models.

BACKGROUND: Key challenges in leveraging unstructured clinician notes for predictive models include ...

Resveratrol ameliorates sepsis-induced immune dysfunction by targeting GADD45A to maintain hematopoietic stem cell homeostasis: A predictive study integrating ensemble machine learning, single-cell transcriptomics, and molecular dynamics simulation.

OBJECTIVE: To investigate the potential pharmacological mechanisms of resveratrol (RES) in ameliorat...

Machine learning prediction model for delirium after heart valve replacement with cardiopulmonary bypass: A large-scale cohort study.

OBJECTIVE: Postoperative delirium (POD) is a common and severe complication following heart valve re...

Respiratory sound analysis for ICU clinical decision support: deep learning-based classification of normal and abnormal sounds using real ICU data.

Integrative multi-omics and machine learning identify mitochondrial biomarkers for pathogen-specific sepsis stratification and translational prioritization.

BACKGROUND: Sepsis is a leading cause of critical illness and mortality, yet substantial heterogenei...

Explore Thermal and Mechanical Properties of Biobased Polyurethane Elastomers Through Machine Learning Models.

Mechanical and thermal properties are the core to determine the application scenarios of biobased po...

Field Foresight-Predicting the Need for Massive Transfusion, ICU Utilization, and Mechanical Ventilation for Traumatically Injured Patients.

INTRODUCTION: Expeditiously predicting outcomes is essential to allocating blood and intensive care ...

Harnessing the gut-heart axis for cardiovascular drug innovation: microbiome, metabolites, and personalized treatment strategies.

Cardiovascular disease (CVD) remains the leading cause of mortality worldwide despite major advances...

Speech-to-Speech Voice-Cloning Care (SVCC) for improving ICU-acquired anxiety for critically ill patients in a tertiary hospital in Beijing, China: protocol of a randomised, controlled trial.

INTRODUCTION: Intensive care unit (ICU) visiting restrictions in hospitals, implemented due to infec...

Accuracy, quality, and readability analyses of responses from large language models to questions on pediatric dental sedation.

Association between deep learning-based atrial fibrillation burden and in-hospital mortality.

Despite its clinical significance, research on atrial fibrillation (AF) burden as a dynamic, real-ti...

Predictive accuracy of Early Warning Score Systems for Detecting Critically Ill Patients in an Outpatient Setting.

Background No systematic methods exist for triaging outpatients with severe conditions. Our previous...

Development and multicenter validation of an explainable machine learning diagnostic criteria for pediatric abdominal sepsis.

Accurate identification of early pediatric abdominal sepsis (PAS) is essential to improving outcomes...

Evaluating deep learning sepsis prediction models in ICUs under distribution shift: a multi-centre retrospective cohort study.

Sepsis prediction models trained on ICU data often fail to generalize under external validation beca...

ARIMA-based forecasting of cerebral physiologic signals in acute traumatic brain injury: a CAnadian high-resolution TBI (CAHR-TBI) cohort study.

BACKGROUND: Traumatic brain injury (TBI) remains a major global health issue, with limited progress ...

Exploring the Ethical Dimensions of AI-Driven Patient Monitoring in Critical Care Nursing: A Systematic Review.

BACKGROUND: Artificial intelligence (AI) is increasingly applied in intensive care units (ICUs) to e...