Critical Care

Artificial Intelligence-Assisted Triage in Emergency Departments: A Scoping Review of Clinical Applications, Outcomes, and Implementation Challenges.

OBJECTIVE: Emergency department (ED) triage determines patient prioritization, early risk recognition, and allocation of limited resources. Artificial intelligence (AI) has been explored to support triagerelated decision-making, but the evidence remains heterogeneous. This scoping review aimed to map applications of AI-assisted triage in EDs and summarize reported outcomes, safety, equity, and imp...

[Advances in multi-source medical data-driven identification and spatiotemporal cluster analysis of acute respiratory infections].

Acute respiratory infections (ARIs) are characterized by high morbidity, strong transmissibility, and non-specific clinical manifestations, posing substantial challenges to conventional single-source surveillance systems for early warning. This review systematically summarizes recent advances in ARIs identification and spatiotemporal cluster analysis based on multi-source medical data, focusing on...

BMI-based prediction models for short-term and long-term mortality following coronary artery bypass grafting using the MIMIC-IV database: a retrospective cohort study.

OBJECTIVE: This study aims to evaluate the relationship between obesity (measured by Body Mass Index (BMI)) and postoperative mortality in patients un...

Explainable deep learning for early sepsis detection from ICU time-series data using XAI techniques.

Sepsis is one of the most deadly illnesses with a high risk of mortality. Consequently, identifying it at the beginning of illness symptoms is crucial...

Physics-informed interaction modeling for warning targeting in multi-risk driving scenarios.

In multi-risk traffic, a warning is valuable only if it directs the driver's limited attention to the right interaction counterpart early enough to pr...

An Adaptive Spatiotemporal Graph Transformer for Multi-Site PM2.5 Multi-Step Forecasting with Non-stationary and Sparse-Aware Method.

Fine particulate matter (PM2.5) concentration is a critical indicator of air quality and is closely related to human health and ecological environment...

Geometry-Encoded Programmable Mechanics in Single-Material Dual-Phase Metamaterials.

Programmable metamaterials that exhibit prescribed mechanical responses and adaptive deformation under external loading are highly desirable for multi...

Longitudinal Changes in Acid-Base Parameters From Dialysis Initiation to Death in Maintenance Hemodialysis Patients.

INTRODUCTION: Blood gas analysis is routinely performed in hemodialysis patients to monitor acid-base status and serum potassium. Despite frequent tes...

An Interpretable Machine Learning Model for Continuous Prediction of Acute Kidney Injury in Critically Ill Patients With Atrial Fibrillation.

The occurrence of acute kidney injury (AKI) in hospitalized patients with atrial fibrillation (AF) significantly increases the mortality risk. Current...

Early Identification of Recovery Potential After Acute Brain Injury Using Functional Near-Infrared Spectroscopy.

BACKGROUND: Accurate early prognostication in patients with acute brain injury remains a major challenge in neurocritical care. Conventional bedside a...

Retraction notice to "Essential blood molecular signature for progression of sepsis-induced acute lung injury: Integrated bioinformatic, single-cell RNA Seq and machine learning analysis" [Int. J. Biol. Macromol. 282 (2024) 136961].

Continuous imputation of blood gas and metabolic panel laboratory values in the intensive care unit using machine learning.

We developed machine learning (ML) models to perform continuous hourly prediction of arterial blood gas (ABG) and basic metabolic panel (BMP) laborato...

Adjustment set selection for estimating optimal treatment rules under confounding.

There is an increasing call for individualized treatment rules, which leverage individual patient characteristics to recommend treatments or intervent...

From Lab to Fab: Path Forward for Multi-Scale Design of Industrial Anion Exchange Membrane Electrolyzers.

Anion exchange membrane water electrolysis (AEMWE) has emerged as a pivotal pathway bridging laboratory-scale research to large-scale hydrogen product...

clinTALL: machine learning-driven multimodal subtype classification and treatment outcome prediction in pediatric T-ALL.

BACKGROUND: Childhood T-lineage acute lymphoblastic leukemia (T-ALL) is an aggressive hematologic malignancy with poor prognosis. Differently from B-c...

A multi-outcome prognostic score for therapeutic responses in multiple sclerosis.

Multiple sclerosis (MS) is marked by heterogeneous disease activity, progression, and therapeutic response. Here, we developed a prognostic score base...

Predicting miRNA-disease associations based on adaptive neighborhood propagation and feature spatial recombination.

MicroRNAs (miRNAs) are critical regulators in biological processes such as cell proliferation, differentiation, and apoptosis, with their aberrant exp...

Post COVID-19 condition diagnosis among older people: findings from Swedish national register data.

INTRODUCTION: Post COVID-19 condition (PCC) denotes the persistence of symptoms following Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)...

Artificial intelligence risk prediction model for common respiratory pathogens in China based on heterogeneous multi-source clinical and geographic data: A modeling study.

Most respiratory pathogens exhibit distinct seasonal and periodic outbreak patterns driven by climatic factors. However, predictive models that jointl...

Association of preoperative monocyte level with postoperative delirium in patients receiving cardiac surgery under propofol-based anesthesia: a retrospective study.

BACKGROUND: Postoperative delirium is a common complication after cardiac surgery, and perioperative inflammation may contribute to its development. H...