Critical Care

WormSpot: a machine learning-powered viability scoring platform in C. elegans for Candida pathogenicity studies.

UNLABELLED: Invasive Candida infections pose a critical health challenge, exacerbated by emerging antifungal resistance. Caenorhabditis elegans (C. elegans) offers a genetically tractable and scalable model for studying Candida pathogenicity, yet conventional viability assays remain labor-intensive, limiting high-throughput applications. In this study, we developed a machine learning-driven worm v...

Wheeze detection in real-world pediatric care: AI applied to smartphone lung auscultation.

UNLABELLED: Smartphone-based lung auscultation, combined with artificial intelligence (AI), may offer a promising alternative for pediatric respiratory telemonitoring. The aim of our study was to evaluate the performance of an AI model on wheeze detection from pediatric respiratory sounds recorded via smartphone. An observational cross-sectional study was conducted at the Pediatric Department of a...

Associations of Red Blood Cell Distribution Width-Derived Indicators and Their Longitudinal Dynamic Trajectories With Mortality Risk in Critically Ill Patients With Pulmonary Hypertension.

Red blood cell distribution width (RDW)-derived indicators have increasingly been recognized as biomarkers reflecting systemic inflammation and hemato...

Screening of Sepsis Diagnostic Biomarkers Based on Fumarate Metabolism-Related Genes with Analysis of Immune Infiltration and Subtype Identification.

BACKGROUND: Sepsis is a major global health challenge characterized by a complex pathogenesis involving an early hyperinflammatory phase followed by a...

Predicting 28-day all-cause mortality in critically ill ischemic stroke patients using white blood cell-to-hemoglobin ratio and dual-feature selection machine learning models.

BACKGROUND: The white blood cell-to-hemoglobin ratio (WHR) is a composite biomarker of inflammation and nutrition, but its prognostic role in critical...

Machine learning-based integration of respiratory oscillometry and spirometry for predicting clinical outcomes in spinal muscular atrophy.

UNLABELLED: Assessing respiratory function in spinal muscular atrophy (SMA) is challenging due to the effort-dependent nature of traditional spirometr...

Beyond binary AKI classification: development and external validation of a distributional model predicting serum creatinine and urine output trajectories in ICU patients.

BACKGROUND: Acute kidney injury (AKI) is a frequent, severe complication in the intensive care units (ICU). Existing machine learning models are typic...

VQ-Wave: A Physics-Driven Spatiotemporal Deep Learning Approach for Noncontrast-Enhanced Lung Ventilation and Perfusion MRI.

PURPOSE: To develop a robust deep learning framework for noncontrast-enhanced functional lung MRI, overcoming the limitations of spectral decompositio...

Hyperpolarized 129Xe MRI Features Associated with Interstitial Lung Disease Identified Using an Interpretable Diagnostic Algorithm.

RATIONALE AND OBJECTIVES: Hyperpolarized 129Xe magnetic resonance imaging and spectroscopy (MRI/MRS) have been used to identify numerous imaging and s...

Ventral hernia repair in emergency settings. A machine learning model to predict post-operative complications.

BACKGROUND: Emergency ventral hernia repair remains a challenging procedure due to patient instability, contaminated surgical fields, and heterogeneit...

Inspiratory muscle training devices for chronic lung disease management: current evidence and future directions.

INTRODUCTION: Inspiratory muscle training (IMT) is a potential adjunct therapy to improve inspiratory muscle strength and endurance, exercise capacity...

Heterojunction-Engineered Mass Spectrometry Platform for Deciphering Serum Metabolic Fingerprints in Diagnosis of Respiratory Diseases.

Respiratory diseases, including bronchial asthma (BA), chronic obstructive pulmonary disease (COPD), interstitial lung disease (ILD), and lung cancer ...

Age-related differences in surgical outcomes for traumatic central cord syndrome: a multi-institutional causal machine learning analysis.

OBJECTIVE: Traumatic central cord syndrome (TCCS) is the most common incomplete spinal cord injury, yet the optimal management strategy remains contro...

Agentic GPT-5.0 system outperforms standard large language models and human experts in critical care clinical decision-making: a simulation study.

BACKGROUND: Agentic artificial intelligence (AI) systems employing multi-model architectures with iterative reasoning may surpass standard single-mode...

NeuroPred-GMC: a dual-branch deep learning architecture for neuropeptide prediction based on gated dilated convolutional network and multi-scale convolutional network.

Neuropeptides are multifunctional signaling molecules in the nervous system. By modulating synaptic transmission and integrating physiological systems...

Metabolomics and Artificial Intelligence (AI) assisted metabolomics in the diagnosis of non-tuberculous mycobacterial infections: progress and challenges.

BACKGROUND: Non tuberculous mycobacterial (NTM) infections are caused in individuals who are immunocompromised or with certain lung conditions. The NT...

IHM-DDI: Integrating High-order Interaction Topology and Morgan Fingerprint Features for Drug-Drug Interaction Prediction.

Drug-drug Interaction (DDI) prediction is crucial in pharmacology and clinical applications. Conventional methods remain constrained by single-view pa...

A Novel, Interpretable Machine Learning Model Predicts Furosemide Dosing After Congenital Cardiac Surgery.

Fluid overload is common after neonatal congenital cardiac surgery (CCS) and is frequently managed with continuous furosemide infusions requiring iter...

A temporal deep learning algorithm for prediction of extubation failures in critical care patients.

Extubation failure in ICU patients is associated with poor outcomes. Existing prediction models often rely on static data, missing dynamic disease flu...

Cough Audio Recognition for Early Detection of Respiratory Diseases: Algorithm Development and Validation Study.

BACKGROUND: Coughing is a common clinical symptom and a protective respiratory reflex closely associated with various respiratory system diseases. The...