Critical Care

Development of an Arterial Carbon Dioxide Estimation Model Using End-Tidal Carbon Dioxide Levels during Surgery in the Pediatric Population.

BACKGROUND: Intraoperative arterial carbon dioxide partial pressure monitoring is essential for pedi...

Integrated toxicological analysis links air pollution-associated acute respiratory distress syndrome signatures to benzo[a]pyrene-induced acute lung injury.

Acute respiratory distress syndrome (ARDS) is associated with high mortality, and increasing evidenc...

Post-Pandemic Forecasting of Pediatric Acute Respiratory Infections with Deep Learning: A Multi-Pathogen, Multi-Time-Horizon Study.

BACKGROUND: Acute respiratory infections (ARIs) remain a major cause of morbidity and hospitalizatio...

Artificial intelligence and the future of telemonitoring in home mechanical ventilation.

Artificial intelligence for telemonitoring in home mechanical ventilation https://bit.ly/4q9XxCa.

Implementing Digital Respiratory Technologies for People With Respiratory Conditions: Scoping Review.

BACKGROUND: Digital health offers opportunities for safe, equitable, and accessible care, and its in...

Reply - Letter to the editor: Comment on "Explainable Electronic Medical Record-Based Machine Learning to Predict 1-Year Incident Protein-Energy Wasting in Non-Dialysis Chronic Kidney Disease: A Single-Center Development Study".

Aligning neonatal sepsis triage diagnostics with WHO target product profiles in low- and middle-income countries.

Neonatal sepsis is a leading cause of infant morbidity and mortality in low- and middle-income count...

Optimizing drug discovery through long short-term memory recurrent neural networks (LSTM RNNs): A hybrid multi-modal framework.

Drug discovery is a resource intensive and time consuming process, signifying a need for machine lea...

Prediction of intensive care unit requirement and in-hospital mortality in Fournier's gangrene: a comparative analysis of conventional statistical and machine learning models.

This study aimed to evaluate the need for intensive care unit (ICU) admission and identify factors a...

Advancing Continuous KRT Education: Simulation and Technology-Enhanced Learning in Contemporary Practice.

Continuous renal replacement therapy (CRRT) is a technically complex, high-risk ICU therapy in which...

Physics-Informed Koopman-Constrained Implicit Q-Learning for Safe Offline Reinforcement Learning in Mechanical Ventilation.

Mechanical ventilation management in intensive care units requires continuous optimization of ventil...

Comment on "Explainable Electronic Medical Record-Based Machine Learning to Predict 1-Year Incident Protein-Energy Wasting in Non-Dialysis Chronic Kidney Disease: A Single-Center Development Study".

Integrated Multi-Omics Analysis and Experimental Validation Identify BCAT1 as a Critical Driver of Hepatocyte Pyroptosis in Acute-On-Chronic Liver Failure.

Acute-on-chronic liver failure (ACLF) is characterized by profound metabolic dysfunction and high mo...

Embedding LLMs in the patient portal to summarize acute minor illness information: a three-arm experimental study.

BACKGROUND: Patient portals provide direct access to clinical encounter data; however, comprehension...

Predicting major adverse cardiovascular and cerebrovascular events in chronic heart failure: a machine learning study.

BACKGROUND: Heart failure (HF) is a clinical syndrome characterized by impaired cardiac diastolic an...

Zero-Shot Self-Supervised Learning of Single Breath-Hold Magnetic Resonance Cholangiopancreatography (MRCP) Reconstruction.

PURPOSE: To investigate the feasibility of zero-shot self-supervised learning reconstruction for red...

Lactate-Associated Gene Signatures as Predictors: A Comprehensive Analysis of Immune Profiles in Sepsis.

BackgroundSepsis is a complex disorder characterized by a dysregulated immune response to infection....

Integrative transcriptomic and bioinformatic analyses predict candidate EMT-related genes in sepsis-associated acute lung injury.

Sepsis-associated acute lung injury (sepsis-ALI) is a complex pathological condition; its underlying...

A multidimensional risk prediction framework for malignant intestinal obstruction based on machine learning: computational model development and clinical validation.

Malignant intestinal obstruction (MIO) is a severe complication of advanced cancer. Traditional stat...

Large language models for optimizing clinical trial recruitment in ICUs: application to ventilator-induced diaphragm dysfunction.

BACKGROUND: Ventilator-induced diaphragm dysfunction (VIDD) is a frequent and under-recognized conse...

Computational tools for personalizing treatment of acute respiratory failure, from machine learning to digital twins: a narrative review.

Patient-specific computational tools hold great promise for the development of more personalized tre...