Emergency Medicine

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

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Interpretable prediction of acute ischemic stroke after hip fracture in patients 65 years and older based on machine learning and SHAP.

BACKGROUND: Hip fracture and acute ischemic stroke (AIS) are prevalent conditions among the older po...

The potential benefit of artificial intelligence regarding clinical decision-making in the treatment of wrist trauma patients.

PURPOSE: The implementation of artificial intelligence (AI) in health care is gaining popularity. Ma...

Artificial intelligence in paediatric head trauma: enhancing diagnostic accuracy for skull fractures and brain haemorrhages.

Pediatric head trauma is a significant cause of morbidity and mortality, with children, particularly...

Deep Learning-Based Denoising Enables High-Quality, Fully Diagnostic Neuroradiological Trauma CT at 25% Radiation Dose.

RATIONALE AND OBJECTIVES: Traumatic neuroradiological emergencies necessitate rapid and accurate dia...

The Potential Clinical Utility of an Artificial Intelligence Model for Identification of Vertebral Compression Fractures in Chest Radiographs.

PURPOSE: To assess the ability of the Annalise Enterprise CXR Triage Trauma (Annalise AI Pty Ltd, Sy...

Editorial Commentary: The Scope of Medical Research Concerning ChatGPT Remains Limited by Lack of Originality.

There is no shortage of literature surrounding ChatGPT and whether this large language model can pro...

Machine Learning-Based Prediction of Chronic Shunt-Dependent Hydrocephalus After Spontaneous Subarachnoid Hemorrhage.

BACKGROUND: Chronic posthemorrhagic hydrocephalus often arises following spontaneous subarachnoid he...

Squid-Inspired Anti-Salt Skin-Like Elastomers With Superhigh Damage Resistance for Aquatic Soft Robots.

Cephalopod skins evolve multiple functions in response to environmental adaptation, encompassing non...

The effects of applying artificial intelligence to triage in the emergency department: A systematic review of prospective studies.

INTRODUCTION: Accurate and rapid triage can reduce undertriage and overtriage, which may improve eme...

Subject-level spinal osteoporotic fracture prediction combining deep learning vertebral outputs and limited demographic data.

UNLABELLED: Automated screening for vertebral fractures could improve outcomes. We achieved an AUC-R...

Reconfiguration of uncertainty: Introducing AI for prediction of mortality at the emergency department.

The promise behind many advanced digital technologies in healthcare is to provide novel and accurate...

Self-supervised learning of wrist-worn daily living accelerometer data improves the automated detection of gait in older adults.

Progressive gait impairment is common among aging adults. Remote phenotyping of gait during daily li...

Hematoma expansion prediction in intracerebral hemorrhage patients by using synthesized CT images in an end-to-end deep learning framework.

Spontaneous intracerebral hemorrhage (ICH) is a type of stroke less prevalent than ischemic stroke b...

The Accuracy of Artificial Intelligence Models in Hand/Wrist Fracture and Dislocation Diagnosis: A Systematic Review and Meta-Analysis.

BACKGROUND: Early and accurate diagnosis is critical to preserve function and reduce healthcare cost...

Prospective Evaluation of Artificial Intelligence Triage of Intracranial Hemorrhage on Noncontrast Head CT Examinations.

Retrospective studies evaluating artificial intelligence (AI) algorithms for intracranial hemorrhag...

Prediction of transfusion risk after total knee arthroplasty: use of a machine learning algorithm.

INTRODUCTION: Total knee arthroplasty (TKA) carries a significant hemorrhagic risk, with a non-negli...

Better Rough Than Scarce: Proximal Femur Fracture Segmentation With Rough Annotations.

Proximal femoral fracture segmentation in computed tomography (CT) is essential in the preoperative ...

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