Critical Care

Critical Care-Specific vs General-Purpose Large Language Models in Emergency Intensive Care Unit Diagnosis: Single-Center Retrospective Paired Comparative Study.

BACKGROUND: The emergency intensive care unit (EICU) manages the most critically ill patients, where rapid and accurate diagnosis is essential yet challenging. Diagnostic error rates in this setting are more than twice as high as in general wards, with serious consequences for patient outcomes. Large language models (LLMs) have attracted growing interest as decision-support tools; however, direct ...

Real-world evidence on antibiotic use among privately insured beneficiaries in Saudi Arabia: a retrospective analysis of claims data.

OBJECTIVES: Inappropriate and broad-spectrum antibiotic use contributes to antimicrobial resistance (AMR) and higher healthcare costs. In Saudi Arabia, despite ongoing antimicrobial stewardship efforts, comprehensive real-world evidence on antibiotic prescribing patterns remains limited. This study aimed to evaluate antibiotic prescribing among insured (Daman) beneficiaries in Saudi Arabia and ben...

Corrigendum to "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'' [Clin Nutr ESPEN 74 (2026) 103346].

The impact of data extraction percentage and deep learning-based reconstruction on image quality in gated PET/computed tomography.

BACKGROUND: Respiratory motion artifacts degrade PET/computed tomography (PET/CT) image quality. Data-driven gated (DDG) PET/CT addresses this issue b...

Heterogeneous Treatment Effects of Renal Replacement Therapy in Critically Ill Patients: A Multicenter Observational Study Using a Japanese ICU Registry.

OBJECTIVE: Randomized trials evaluating the timing of renal replacement therapy (RRT) have informed current practice toward more conservative initiati...

Artificial Intelligence, Machine Learning, and Multi-Omics Biomarker Discovery in Ectopic Pregnancy: A Comprehensive Review.

BACKGROUND: Ectopic pregnancy is a major cause of first-trimester maternal morbidity and mortality, with diagnosis and management posing persistent cl...

Automated Features, Algorithms, and Technologies of Electronic Early Warning/Track-and-Trigger Systems: Systematic Review.

BACKGROUND: Electronic early warning/track-and-trigger systems (EW/TTS) are crucial for patient monitoring, detecting clinical deterioration (CD), and...

TempoSafe-CVS: A Temporal Multi-scale Deep Learning Framework for Automated Assessment of the Critical View of Safety in Laparoscopic Cholecystectomy.

Accurate assessment of the critical view of safety (CVS) is essential for preventing bile duct injuries during laparoscopic cholecystectomy. Existing ...

Large language models in respiratory care: safety and clinical integration.

BACKGROUND: Large language models (LLMs) are rapidly entering respiratory medicine workflows. Their clinical role remains unclear. A central concern i...

Machine learning-assisted prediction of 5-year mortality in chronic kidney disease: the KoreaN cohort study for Outcome in patients With Chronic Kidney Disease (KNOW-CKD).

BACKGROUND: Mortality prediction models for patients with non-dialysis chronic kidney disease (CKD) remain limited despite their clinical importance. ...

Surface-enhanced Raman scattering for the diagnosis of respiratory viruses.

Surface-enhanced Raman scattering (SERS) has become a promising tool for rapid and sensitive respiratory pathogen detection. However, relevant reviews...

Privacy-Preserving Framework for Multi-Institutional Medical Time-Series Analysis via Homomorphic Encryption: Design and Development Study.

BACKGROUND: The development of robust medical AI for knowledge discovery and decision support commonly necessitates large-scale datasets from multiple...

Auditable unit-aware thresholds in symbolic regression via logistic-gated operators.

Symbolic regression offers the promise of readable equations but often struggles to represent unit-aware thresholds that drive clinical decisions. We ...

Calibration-Free Estimation of Cerebrovascular Reactivity From Resting-State BOLD fMRI Using Reconstructed Respiratory Fluctuations.

PURPOSE: Cerebrovascular reactivity (CVR) provides an important index of vascular health and is conventionally quantified using a hypercapnic gas or b...

Identifying GADD45A as a potential R-loop regulator in sepsis via machine-learning and multi-omics analysis.

BACKGROUND: Sepsis is a life-threatening syndrome characterized by dysregulated immune responses, while the molecular basis of immune dysfunction rema...

Assessment and validation of the established free-running framework for cardiac function by magnetic resonance imaging at 1.5T (FAST-CMR): an international multi-center, multi-vendor study.

BACKGROUND: Cardiovascular magnetic resonance (CMR) is the reference standard for assessing cardiac function, yet its widespread clinical use remains ...

Interpretable Machine Learning Models for Mortality Prediction in Critically Ill Patients with Intra-Aortic Balloon Pump Therapy: Development and Evaluation.

BACKGROUND: This study aims to develop and validate predictive models to assess mortality risk among patients undergoing intra-aortic balloon pump (IA...

Identification of obesity risk factors in 3-12-year-old children and adolescents with prior respiratory tract infections via interpretable machine and deep learning models.

BACKGROUNDS AND OBJECTIVES: Childhood obesity and respiratory tract infections (RTIs) are 2 major global public health issues that frequently co-occur...

Admission photoplethysmography-based mortality prediction in hospitalized Ugandan children with suspected or confirmed infection: A feasibility study.

Sepsis remains a major cause of preventable pediatric hospital deaths in developing countries, with progress hindered by the lack of effective risk id...

Point-of-care detection for respiratory diseases: From samples and biomarkers to principles and applications.

Early screening can significantly reduce the severe morbidity and mortality of respiratory diseases and alleviate the burden on public healthcare syst...