Emergency Medicine

A survey of patient acceptability of the use of artificial intelligence in the diagnosis of paediatric fractures: an observational study.

INTRODUCTION: This study aimed to assess carer attitudes towards the use of artificial intelligence ...

Deep Learning during burn prehospital care: An evolving perspective.

Harnessing the Power of Generative AI for Clinical Summaries: Perspectives From Emergency Physicians.

STUDY OBJECTIVE: The workload of clinical documentation contributes to health care costs and profess...

Artificial intelligence in the diagnosis and treatment of acute appendicitis: a narrative review.

Artificial intelligence is transforming healthcare. Artificial intelligence can improve patient care...

Deciphering the Lexicon of Protein Targets: A Review on Multifaceted Drug Discovery in the Era of Artificial Intelligence.

Understanding protein sequence and structure is essential for understanding protein-protein interact...

Regenerative rehabilitation measures to restore tissue function after arsenic exposure.

Environmental exposure of arsenic impairs the cardiometabolic profile, skeletal muscle health, and n...

The future of burn management: How can machine learning lead to a revolution in improving the rehabilitation of burn patients?

Investigating the Aryl Hydrocarbon Receptor Agonist/Antagonist Conformational Switch Using Well-Tempered Metadynamics Simulations.

The aryl hydrocarbon receptor (AhR) is a ligand-dependent transcription factor that mediates biologi...

A machine learning algorithm-based predictive model for pressure injury risk in emergency patients: A prospective cohort study.

OBJECTIVES: To construct pressure injury risk prediction models for emergency patients based on diff...

Design and testing of ultrasound probe adapters for a robotic imaging platform.

Medical imaging-based triage is a critical tool for emergency medicine in both civilian and military...

Deep learning-based harmonization of trabecular bone microstructures between high- and low-resolution CT imaging.

BACKGROUND: Osteoporosis is a bone disease related to increased bone loss and fracture-risk. The var...

Comparison of an Ensemble of Machine Learning Models and the BERT Language Model for Analysis of Text Descriptions of Brain CT Reports to Determine the Presence of Intracranial Hemorrhage.

UNLABELLED: is to train and test an ensemble of machine learning models, as well as to compare its ...

Development of a deep learning model that predicts critical events of pediatric patients admitted to general wards.

Early detection of deteriorating patients is important to prevent life-threatening events and improv...

Brain is also time: good short-term outcome predictions of artificial intelligence in spontaneous intracerebral hemorrhage pave the way for the long-term assessment.

Desired clinical applications of artificial intelligence in emergency medicine: A Delphi study.

Prediction of Hematoma Expansion in Intracerebral Hemorrhage in 24 Hours by Machine Learning Algorithm.

OBJECTIVE: The significance of noncontrast computer tomography (CT) image markers in predicting hema...

Real-time machine learning-assisted sepsis alert enhances the timeliness of antibiotic administration and diagnostic accuracy in emergency department patients with sepsis: a cluster-randomized trial.

Machine learning (ML) has been applied in sepsis recognition across different healthcare settings wi...

Effect of robotic gait training on muscle and bone characteristics in spinal cord transected rats.

Osteoporosis and loss of muscle mass are secondary issues with spinal cord injury. Robotic gait trai...

Accuracy of automated segmentation and volumetry of acute intracerebral hemorrhage following minimally invasive surgery using a patch-based convolutional neural network in a small dataset.

PURPOSE: In cases of acute intracerebral hemorrhage (ICH) volume estimation is of prognostic and the...

Deep Learning for Automated Detection and Localization of Traumatic Abdominal Solid Organ Injuries on CT Scans.

Computed tomography (CT) is the most commonly used diagnostic modality for blunt abdominal trauma (B...

Toxicovigilance 2.0 - modern approaches for the hazard identification and risk assessment of toxicants in human beings: A review.

The attempt to define toxicovigilance can be based on defining its fundamental principles: preventio...