Critical Care

A Multi-center Gadolinium-ethoxybenzyl-diethylenetriamine Pentaacetic Acid (Gd-EOB-DTPA) MRI Dataset with Expert Annotations and clinicopathological data.

Liver resection is a cornerstone treatment for liver tumors, yet post-hepatectomy liver failure (PHLF) remains a severe and life-threatening complication with no effective treatment. Recent advances in artificial intelligence (AI) have shown promise in addressing this challenge; however, progress has been hindered by the limited availability of high-quality, expert-annotated, multi-center datasets...

Association of triglyceride-cholesterol-body weight index with in-hospital mortality in critically ill patients with heart failure.

Malnutrition and metabolic abnormalities are common in patients with heart failure (HF) requiring intensive care unit (ICU) admission and are associated with poor outcomes. This study evaluated the association between triglyceride-cholesterol-body weight index (TCBI) and in-hospital mortality in critically ill patients with HF and developed a machine learning-based model to assess its predictive v...

Integrated cell-free DNA and omics genetic scores for early detection of gestational diabetes: evidence from a nationwide multicenter study.

BACKGROUND: Gestational diabetes mellitus (GDM) affects 15.6% of pregnancies globally, with Vietnam exhibiting one of the highest prevalences at 21%. ...

Lessons from the first U.S. school districts with real-time indoor environmental quality (IEQ) sensors in classrooms: benefits, barriers and opportunities.

With aging buildings, rising temperatures, and limited budgets, school districts in the United States need effective strategies to address classroom e...

Stress hyperglycemia ratio improves 28-day mortality prediction beyond GRACE score in critically ill patients with acute coronary syndrome: a retrospective cohort study from MIMIC-IV.

BACKGROUND: The stress hyperglycemia ratio (SHR) is increasingly recognized as a reliable biomarker for adverse outcomes. However, its prognostic valu...

Enhancing Osteosarcoma Survival Predictions: A Comparative Study of a Multicomponent-Model Machine Learning Approach Integrating SEER and NCDB Data Sets Versus Conventional Single-Data-Set Modeling.

BACKGROUND: Osteosarcoma treatment decisions require accurate prognostic assessment, yet utilization of machine learning (ML) models is problematic be...

A machine learning system enables just-in-time risk-stratified sepsis evaluations in the neonatal intensive care unit.

INTRODUCTION: NICU sepsis evaluation balances rapid antibiotic administration for mortality reduction against unnecessary treatment. Objective risk st...

Explainable machine learning-driven identification of heart failure biomarkers: a multi-model feature selection approach with SHAP-based interpretability.

Heart failure (HF) remains a major clinical challenge due to its complex pathophysiology and the limitations of existing biomarkers. In this study, we...

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.

BACKGROUND: Protein-energy wasting (PEW) is common in chronic kidney disease (CKD) and is linked to poor outcomes. Early risk stratification may enabl...

Targeting Tau-Mitochondrial Crosstalk in Alzheimer's Disease: Integrative Multi-Omics and Artificial Intelligence-Driven Tools for the Development of Disease-Modifying Therapeutics.

Alzheimer's disease (AD) is a progressive neurodegenerative illness marked by cognitive impairment, synaptic dysfunction and neuronal death. Tau prote...

Methods for determining indications for antibiotic prescriptions to facilitate antimicrobial stewardship: a scoping review.

BACKGROUND: Effective antimicrobial stewardship (AMS) requires accurate information on the reason for prescribing antimicrobials. To design targeted i...

Spatio-temporal multi-fault and severity aware diagnosis in WSN via GNN transformers.

Wireless Sensor Networks (WSNs) play a perilous role in the IoT environment and other applications, where reliable sensing and timely fault diagnosis ...

Proactive soft-failure prediction in optical transport networks via physics-inspired features and Infrastructure-as-Code orchestration.

Optical transport networks rely on reactive fault management, which guarantees service disruption during the onset of soft failures. We present a fram...

A multi-domain graph-integrated neural framework for robust acoustic anomaly detection under adverse environmental conditions.

Acoustic event understanding and anomaly detection play a critical role in security monitoring, defence applications, and urban safety, yet current ap...

Comparative evaluation of information quality, readability, and guideline consistency of large language model-generated educational content on hemodialysis complications: a cross-sectional assessment of generative AI-driven chatbots.

BACKGROUND: Large language models are increasingly becoming a key resource for hemodialysis patients to access information on disease management. Howe...

Development of a deep-learning model for classification of intensivists' extubation decisions using ventilator graphic monitor images: a prospective observational study.

BACKGROUND: Timely extubation requires advanced expertise and extensive clinical experience; however, intensive care specialists are scarce globally, ...

Mean airway pressure as an independent risk factor for developing acute kidney injury in mechanically ventilated critically ill patients: a multi-center retrospective analysis.

Mechanical ventilation is a well-recognized risk factor for acute kidney injury (AKI), but the specific role of mean airway pressure (Pmean) remains i...

Geospatial multi-scale GNN for urban food security in climate-stressed environments.

The increasing global food insecurity driven by climate-induced natural hazards and soil degradation has made the resilience of alternative agricultur...

Machine learning-based risk prediction of 28-day mortality for sepsis patients with augmented renal clearance.

Augmented renal clearance (ARC) frequently occurs in critically ill septic patients and is known to impact survival outcomes. To address this, we aime...

PickAMoo: LIDAR-enhanced mask R-CNN segmentation for precision weight estimation in dairy cattle using smartphone imaging.

Data on body weight, as well as objective measures of body condition and size, are essential for appropriate decision-making on farm level, for exampl...