Emergency Medicine

Latest AI and machine learning research in emergency medicine for healthcare professionals.

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Showing 2920-2940 of 4,986 articles
WristMIR: Coarse-to-Fine Region-Aware Retrieval of Pediatric Wrist Radiographs with Radiology Report-Driven Learning

Retrieving wrist radiographs with analogous fracture patterns is challenging because clinically impo...

Unseen Insights: An AI-Powered Exploration of Secure Patient Messages in Ophthalmology

Objective To characterize the clinical and administrative concerns communicated through secure ophth...

Development and internal validation of risk scores to predict survival in the pediatric population following in-hospital cardiac arrest.

Introduction In-hospital cardiac arrest (IHCA) in the pediatric population is associated with poor s...

Rare Event Early Detection: A Dataset of Sepsis Onset for Critically Ill Trauma Patients

Sepsis is a major public health concern due to its high morbidity, mortality, and cost. Its clinical...

STEER: Inference-Time Risk Control via Constrained Quality-Diversity Search

Large Language Models (LLMs) trained for average correctness often exhibit mode collapse, producing ...

Toxicity Assessment in Preclinical Histopathology via Class-Aware Mahalanobis Distance for Known and Novel Anomalies

Drug-induced toxicity remains a leading cause of failure in preclinical development and early clinic...

Semantically Aware UAV Landing Site Assessment from Remote Sensing Imagery via Multimodal Large Language Models

Safe UAV emergency landing requires more than just identifying flat terrain; it demands understandin...

Development and implementation of an AI system for clinical toxicology sign-outs

Modern natural language tools have potential to improve clinical workflows, but few have been succes...

Predicting Intermittent Job Failure Categories for Diagnosis Using Few-Shot Fine-Tuned Language Models

In principle, Continuous Integration (CI) pipeline failures provide valuable feedback to developers ...

Structure-constrained Language-informed Diffusion Model for Unpaired Low-dose Computed Tomography Angiography Reconstruction

The application of iodinated contrast media (ICM) improves the sensitivity and specificity of comput...

Automated Echocardiographic Detection of Congenital Heart Disease Using Artificial Intelligence

Background: Delayed or missed diagnosis of congenital heart disease (CHD) contributes to excess pedi...

RareAlert: Aligning heterogeneous large language model reasoning for early rare disease risk screening

Missed and delayed diagnosis remains a major challenge in rare disease care. At the initial clinical...

Predicting the need for medical care after toxin exposure using SHAP-interpretable gradient boosting

Objective: Experts in poison control centers must accurately and efficiently assess the severity of ...

From Volumes to Slices: Computationally Efficient Contrastive Learning for Sequential Abdominal CT Analysis

The requirement for expert annotations limits the effectiveness of deep learning for medical image a...

RANDSMAPs: Random-Feature/multi-Scale Neural Decoders with Mass Preservation

We introduce RANDSMAPs (Random-feature/multi-scale neural decoders with Mass Preservation), numerica...

Tracing 3D Anatomy in 2D Strokes: A Multi-Stage Projection Driven Approach to Cervical Spine Fracture Identification

Cervical spine fractures are critical medical conditions requiring precise and efficient detection f...

Organ-Aware Attention Improves CT Triage and Classification

There is an urgent need for triage and classification of high-volume medical imaging modalities such...

Creating a scalable CT yield metric for pulmonary embolisms in the emergency department using an open-source large language model

BackgroundCT scans are the gold-standard diagnostic test for pulmonary embolisms (PE). Despite stabl...

Predictive Modeling of Healthcare Workers' Priorities of WHO 2030 Key Activities for Snakebite Prevention and Control in Ghana

Snakebite is a neglected public health problem that results in significant morbidity and mortality, ...

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