Emergency Medicine

Better Blood Pressure Control for Stroke Patients in the ICU: A Deep Reinforcement Learning with Supervised Guidance Approach for Adaptive Infusion Rate Tuning.

Blood pressure variability (BPV) plays a critical role in vascular diseases, particularly in acute i...

Improving Emergency Department Visit Risk Prediction: Exploring the Operational Utility of Applied Patient Portal Messages.

Patient portal messages represent a unique source of clinical data due to how they represent the voi...

Applications of Artificial Intelligence and Machine Learning in Emergency Medicine Triage - A Systematic Review.

BACKGROUND: Overcrowding in Emergency departments adversely impacts efficiency, patient outcomes, an...

Transforming emergency triage: A preliminary, scenario-based cross-sectional study comparing artificial intelligence models and clinical expertise for enhanced accuracy.

INTRODUCTION: This study examines triage judgments in emergency settings and compares the outcomes o...

E-validation - Unleashing AI for validation.

The validation of new approach methods (NAMs) in toxicology faces significant challenges, including ...

Advanced Machine Learning Models for Predicting Post-Thrombolysis Hemorrhagic Transformation in Acute Ischemic Stroke Patients: A Systematic Review and Meta-Analysis.

Thrombolytic therapy is essential for acute ischemic stroke (AIS) management but poses a risk of he...

An Innovative Deep Learning Approach to Spinal Fracture Detection in CT Images.

AIM: Spinal fractures, particularly vertebral compression fractures, pose a significant challenge in...

Hemi-diaphragm detection of chest X-ray images based on convolutional neural network and graphics.

BACKGROUND: Chest X-rays (CXR) are widely used to facilitate the diagnosis and treatment of critical...

Prosthetically driven robot-assisted implant surgery: turning a major failure into a simple case.

This case report presents a challenging case of catastrophic failure of a fixed partial denture invo...

Examination-Level Supervision for Deep Learning-based Intracranial Hemorrhage Detection on Head CT Scans.

Purpose To compare the effectiveness of weak supervision (ie, with examination-level labels only) an...

A CT-based Deep Learning Model for Predicting Subsequent Fracture Risk in Patients with Hip Fracture.

Background Patients have the highest risk of subsequent fractures in the first few years after an in...

Alternative methods go green! Green toxicology as a sustainable approach for assessing chemical safety and designing safer chemicals.

Green toxicology is marching chemistry into the 21st century. This emerging framework will transform...

Development and validation of an artificial intelligence algorithm for detecting vocal cords in video laryngoscopy.

Airway procedures in life-threatening situations are vital for saving lives. Video laryngoscopy (VL)...

[Application and prospect of machine learning in orthopaedic trauma].

OBJECTIVE: To review the current applications of machine learning in orthopaedic trauma and anticipa...

The Natural Language Artificial Intelligence Revolution in Emergency Medicine: Unleash the Potential, Addressing the Concerns.

A Sober Appraisal of Artificial Intelligence Systems, Particularly ChatGPT, in the Facets of Emergency Medicine.

Efficacy comparison between iliosacral screw fixation of the posterior pelvic ring fracture with the assistance of modified percutaneous three-dimensional printing guide template and conventional fluoroscopy.

OBJECTIVES: The effect of three-dimensional (3D) printed bone-attached guide plate assisted cannulat...

Artificial intelligence assistance in deciding management strategies for polytrauma and trauma patients.

<b><br>Introduction:</b> Artificial intelligence (AI) is an emerging technology wi...

[Application and research progress of artificial intelligence technology in trauma treatment].

OBJECTIVE: To review the application and research progress of artificial intelligence (AI) technolog...

Robust Multi-View Fracture Detection in the Presence of Other Abnormalities Using HAMIL-Net.

INTRODUCTION: Foot and ankle fractures are the most common military health problem. Automated diagno...

Autonomous Multi-modality Burn Wound Characterization using Artificial Intelligence.

INTRODUCTION: Between 5% and 20% of all combat-related casualties are attributed to burn wounds. A d...