Intensivists

Mastering Complexity toward High-Performance Multi-Principal Element Alloy-Based Films and Coatings: A Review on Microstructural Regulation and Property Optimization.

Multi-principal element alloy (MPEA)-based films and coatings are redefining the boundaries of mater...

High-fidelity "top-down" DLP bioprinting of multi-material soft tissue constructs enabled by computer vision-based layer control.

Bioprinting continues to redefine the frontiers of regenerative medicine by enabling the fabrication...

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...

Unveiling the prognostic and therapeutic landscape of the zinc transporter protein SLC39A family in colorectal cancer through multi-omics and machine learning approaches.

Colorectal cancer (CRC) remains a significant global health challenge due to its high prevalence and...

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...

Visual guided AI color art image generation using enhanced GAN.

With the improvement of material living standards, the application of Artificial Intelligence techno...

Bioinspired Auxetic Metastructures Enable Biomechanically Adaptive, Machine Learning-Enhanced Self-Powered Sensing with Ultrahigh Efficiency.

Self-powered flexible sensors exhibit revolutionary potential in next-generation wearable technologi...

Prediction-guided clustering for sepsis phenotyping: a retrospective cohort analysis.

BACKGROUND: Sepsis is a major cause of morbidity and mortality worldwide, with its heterogeneous and...

Development and validation of an artificial intelligence-based model for predicting teicoplanin plasma concentrations in intensive care unit patients with pulmonary infections: a retrospective study.

INTRODUCTION: Teicoplanin is widely used to treat pulmonary infections, particularly in critically i...

Development and Validation of Machine Learning Model to Predict Refractory Septic Shock.

This study developed and validated a machine learning model to predict refractory septic shock in pa...

Machine Learning Predicts ICU In-Hospital Mortality in Ards Patients Aged 80 and Above: A Multinational Multicenter Retrospective Study.

BACKGROUND: The present study aims to develop and validate an interpretable machine learning (ML) mo...

Machine learning-assisted Zr-MOFFe@SECHA fluorescence and colorimetric dual-mode intelligent platform for sensitive LPS detection.

BACKGROUND: Lipopolysaccharide (LPS) is a crucial diagnosis biomarker for sepsis. Accurate and sensi...

Representation learning for the prediction of length of stay in infants with congenital heart diseases undergoing cardiac surgery.

AIMS: Congenital heart disease is the most common birth defect and significantly impacts health, mor...

A machine learning-based classification method for SynRM faults.

Synchronous reluctance motors (SynRMs) are increasingly critical in industrial and traction applicat...

Accuracy of Diagnosis and Anticipation of Future Treatment in Pediatric Peripelvic Infections: The Role of Multisurgeon Review and Implications for Future Machine Learning Algorithms.

INTRODUCTION: MRI is commonly used to evaluate pelvic musculoskeletal infections. Limited "quick" MR...

Clinic-first sepsis recognition in the ICU: a proteomics-guided, parsimonious model with independent validation.

BACKGROUND: Sepsis recognition in the ICU remains variable and relies on consensus clinical criteria...

Explainable machine learning for postoperative respiratory failure prediction in open-heart surgery patients - a study based on the MIMIC-IV database.

BACKGROUND: Postoperative respiratory failure (PRF) is a severe complication after open-heart surger...

Machine learning in ARDS: an intensivist's guide to artificial intelligence applications.

Artificial Intelligence Predictions in Huge Chemical Spaces: Chiroptical Properties of [6]-helicene Family.

Navigating the vast chemical space remains a major challenge in the rational design of materials wit...

Functional-based multi-omics early prediction of radiation pneumonitis in NSCLC using AI-generated perfusion and ventilation from planning CT.

ObjectiveThis study aims to develop a functional-based multi-omics model for early prediction of rad...

Systematic review of Artificial Intelligence-based methods for glycemic control and risk prediction in intensive care units.

BACKGROUND: Achieving safe glycemic targets in intensive care remains difficult due to rapidly chang...