Critical Care

Utilization and Feasibility of a Wearable Device in Patients With Sedative Effects of Drugs: Protocol for a Prospective Observational Study for the Advanced Respiratory Monitoring Events in Drug Toxicity (ARM-ED) Study.

BACKGROUND: Drug-related deaths worldwide are most commonly attributed to opioids. Opioids and other...

Analysis of Models to Estimate Morbidity Rates of Respiratory Diseases Through Deep Learning.

Respiratory diseases remain a challenge in Brazil due to socioeconomic inequalities and environmenta...

Cough acoustic analysis using artificial intelligence for COVID-19 detection: A comparative study of patient cohorts from Lima, Peru and Montreal, Canada.

PURPOSE: Digital cough screening for COVID-19 detection shows promise, but population differences in...

DispatchMAS: fusing taxonomy and artificial intelligence agents for emergency medical services.

BACKGROUND: Emergency medical dispatch is a critical, high-stakes process where dispatcher decisions...

Past, present and future perspectives of traumatic brain injury.

Despite extensive research, traumatic brain injury (TBI) imposes significant mortality and morbidity...

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...

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...

Artificial Intelligence-Driven Electrocardiogram Screening for Asymptomatic Left Ventricular Systolic Dysfunction in the General Population.

BACKGROUND: Asymptomatic left ventricular systolic dysfunction (LVSD) is a well-established precurso...

DeePedIMV: Deep learning model for early prediction of invasive mechanical ventilation in critically ill children.

BACKGROUND: Acute deterioration requiring invasive mechanical ventilation (IMV) is common in critica...

Development and Validation of a Machine Learning-Based Nomogram for Predicting Severe Pneumocystis jirovecii Pneumonia in Kidney Transplant Recipients.

BACKGROUND Pneumocystis jirovecii pneumonia (PJP) is a life-threatening opportunistic infection in k...

Comparison of Left Ventricular Ejection Fraction Among 18F-FDG Dual-Gated PET/CT, Single-Gated PET/MRI, and Cardiac MRI.

Left ventricular ejection fraction (LVEF) is a critical parameter in the evaluation of cardiac funct...

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, s...

Current and future contributions of AI to pulmonary function test interpretation, diagnostic approaches, and predictions of disease progression.

INTRODUCTION: Artificial intelligence (AI) methods - including machine learning, deep learning, and ...

Machine Learning Prediction of Progression to Dialysis in Patients With Polycystic Kidney Disease: Population-Based Retrospective Cohort Study.

BACKGROUND: Autosomal dominant polycystic kidney disease (ADPKD), characterized by progressive cyst ...

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.

Prediction of favorable outcomes of acute basilar artery occlusion using machine learning.

BACKGROUND: This study aims to develop an interpretable machine learning model using SHapley Additiv...