Intensivists

Integration of Systemic Immune-Inflammation Index and Lactate for diagnostic and early risk stratification in pediatric sepsis.

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 materials science, offering an unprecedented synergy of mechanical robustness, thermal stability, and chemical resilience. Their performance arises from intrinsic chemical complexity, such as high configurational entropy, lattice distortion, sluggish diffusion, and synergistic elemental interactions, ena...

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 of complex, three-dimensional tissue constructs t...

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 respiratory distress syndrome (ARDS) and their tran...

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 mortality rates. Zinc transporter proteins of the...

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 therapeutic approach in sepsis remain largely unexplored. Th...

Visual guided AI color art image generation using enhanced GAN.

With the improvement of material living standards, the application of Artificial Intelligence technology for generating color art images effectively m...

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 technologies owing to their exceptional sensitivity and self...

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 dynamically evolving clinical presentation compli...

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 ill patients with gram-positive bacterial infection...

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 patients with sepsis admitted to a tertiary care cen...

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) model based on a multicenter cohort, which is intend...

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 sensitive determination of LPS in real samples (human s...

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, mortality, and healthcare costs. Accurately estimatin...

A machine learning-based classification method for SynRM faults.

Synchronous reluctance motors (SynRMs) are increasingly critical in industrial and traction applications due to their high efficiency, magnet-free con...

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" MRI protocols enable timely imaging without intraven...

Interpretable Multi-Modality Consensus QSAR Framework: Integrating Machine and Deep Learning for Enhanced Multi-Endpoint Toxicity Assessment.

Accurate toxicity assessment is essential for chemical safety, but experimental testing is costly, slow, and ethically constrained, motivating the ado...

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 rather than biomarker-defined rules. Routine labo...

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 surgery, associated with increased mortality and prolong...

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