Emergency Medicine

Evaluation of AI developed for rib fracture detection in identifying vertebral fractures on abdominal CT.

PURPOSE: To evaluate the performance of an AI algorithm originally developed for rib fracture detection in identifying vertebral fractures on abdominal CT scans. METHODS: A retrospective study was performed on 58 patients with both CT and MRI scans. An AI model and ER clinicians independently assessed CT images for fractures of the vertebral body, transverse processes, and spinous processes. Two s...

The diagnostic accuracy of artificial intelligence in detecting foot and ankle fractures: a systematic review and meta-analysis of diagnostic test accuracy.

INTRODUCTION: Foot and ankle fractures, including radiographically subtle or occult injuries, present a diagnostic challenge in emergency settings, with missed diagnoses causing severe complications. Artificial intelligence (AI), specifically deep learning, offers a promising adjunct for radiographic interpretation. This systematic review and meta-analysis evaluates the diagnostic test accuracy of...

High temperature Nb-Si alloys using data science: optimization of fracture toughness and high-temperature strength.

High temperature Nb-Si based alloys face a critical challenge: achieving adequate room-temperature fracture toughness ( > 18 MPa·m1/2) for processing ...

A 2004-2025 Bibliometric Study of Genetic Variation and Multiomics Biomarkers in Sepsis Based on 940 Publications.

Sepsis is a highly heterogeneous syndrome, and conventional clinical indicators and single biomarkers often fail to capture its biological complexity ...

Pepholin, a bacteriophage holin-derived antimicrobial peptide with membrane-disruptive activity and therapeutic efficacy in MDR Pseudomonas aeruginosa burn wounds.

The emergence of multidrug-resistant (MDR) Pseudomonas aeruginosa poses a serious threat to burn wound healing, necessitating the development of alter...

Decoding the role of phthalate plasticizers (DBP, DOP, and DEHP) in idiopathic pulmonary fibrosis: an integrated network toxicology and machine learning approach.

The molecular mechanism of idiopathic pulmonary fibrosis (IPF) caused by phthalate (PAE) is not well understood, presenting notable clinical and toxic...

Intelligent monitoring system for pipeline status based on MEMS acoustic emission sensors.

Pipeline structural health monitoring is critical for global energy security, yet traditional bulk piezoelectric acoustic emission (AE) sensors are in...

Deep learning integration of initial abdominal radiography and early clinical information for predicting hospitalization of patients with abdominal symptoms.

Abdominal symptoms are a common reason for emergency department visits, yet early admission decisions remain challenging due to limited diagnostic inf...

Artificial Intelligence in Wilderness Search and Rescue: A Narrative Review.

Artificial intelligence (AI) is transforming wilderness Search and Rescue (SAR), where time constraints, austere conditions, and limited personnel hav...

Machine learning for predicting emergency department visits in patients with type 2 diabetes: A real-world, multi-institutional study.

BACKGROUND: Patients with type 2 diabetes mellitus (T2DM) prone to acute diabetic complications are at high risk for emergency department (ED) visits,...

A blood gas parameter-based assessment model for predicting poor prognosis in sepsis: A retrospective analysis of the MIMIC-IV and eICU-CRD.

BACKGROUND: Blood gas parameters are associated with sepsis prognosis. This study aimed to develop an assessment model based on blood gas parameters f...

Struggling to integrate artificial intelligence in prehospital emergency care in a developing country: exploration of the Iranian experts' views based on qualitative content analysis.

INTRODUCTION: The use of integrated artificial intelligence (AI) in prehospital emergency services can not only increase the quality of services, but ...

Cardio-respiratory deep learning model to predict hospital admission from emergency department electrocardiogram images and respiration videos: a prospective study.

BACKGROUND: Early prediction of hospital admission at the emergency department (ED) triage can improve patient flow and resource allocation. Most exis...

Social Determinants of Health and Fentanyl Overdose Mortality Across US Counties: An XGBoost and SHAP Analysis Identifying Silent Risk Counties and Treatment Deserts.

BACKGROUND: Fentanyl overdose deaths are still increasing across the U.S. Even though the crisis is growing, we still do not fully understand which co...

Prompt-Sensitive Decision Behavior of Large Language Models in Intensive Care Unit Mortality Prediction for Spontaneous Intracerebral Hemorrhage: Comparative Benchmarking Study.

BACKGROUND: Large language models (LLMs) are increasingly being explored for clinical decision support. However, whether inference-only LLM outputs ca...

Clinical Triage of Individuals With Warning Symptoms of Imminent Cardiac Arrest.

BACKGROUND: At least 50% of individuals who suffer sudden cardiac arrest (SCA) have warning symptoms before their SCA, but these are not sufficient to...

Machine-Learning-Assisted Catalytic Sensor Array for Rapid Diagnosis of Aortic Dissection.

Acute aortic dissection (AD) is a time-critical cardiovascular emergency that is clinically difficult to distinguish from other causes of acute chest ...

Plasticizer-related toxicogenomic signatures in gestational diabetes: Mendelian randomization, placental single-cell transcriptomics and trophoblast validation.

Plasticizer exposure has been associated with gestational diabetes mellitus (GDM), but the placental toxicogenomic mechanisms that may connect environ...

Prediction of in-hospital cardiac arrest on general wards using calibrated machine learning.

OBJECTIVE: To identify time-windowed clinical predictors of in-hospital cardiac arrest (IHCA) and develop a temporally validated, calibrated machine-l...

3Br-MGD: few-shot toxicity prediction with a three-branch deep encoder and meta-learning framework.

Predicting the toxicity of pharmaceutical compounds remains a major challenge in drug discovery. Early and accurate toxicity assessment is essential f...