Emergency Medicine

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

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Showing 1639-1659 of 5,236 articles
Use of an artificial intelligence-based rule extraction approach to predict an emergency cesarean section.

OBJECTIVE: One of the major problems with artificial intelligence (AI) is that it is generally known...

Development and validation of a deep learning model to screen hypokalemia from electrocardiogram in emergency patients.

BACKGROUND: A deep learning model (DLM) that enables non-invasive hypokalemia screening from an elec...

Physically crosslinked PVA/graphene-based materials/aloe vera hydrogel with antibacterial activity.

Burn is a major skin injury that occurs worldwide. For second-degree burns, special treatment should...

Exposure to polydopamine nanoparticles induces neurotoxicity in the developing zebrafish.

Currently, the potential applications of polydopamine (PDA) nanoparticles in the biomedical field ar...

Machine learning models of ischemia/hemorrhage in moyamoya disease and analysis of its risk factors.

OBJECT: This study aimed to determine the risk factors of ischemic/hemorrhagic stroke in patients su...

CYPlebrity: Machine learning models for the prediction of inhibitors of cytochrome P450 enzymes.

The vast majority of approved drugs are metabolized by the five major cytochrome P450 (CYP) isozymes...

Hybrid deep learning model for risk prediction of fracture in patients with diabetes and osteoporosis.

The fracture risk of patients with diabetes is higher than those of patients without diabetes due to...

Artificial intelligence-enhanced echocardiography in the emergency department.

A focused cardiac ultrasound performed by an emergency physician is becoming part of the standard as...

Applications of machine learning to undifferentiated chest pain in the emergency department: A systematic review.

BACKGROUND: Chest pain is amongst the most common reason for presentation to the emergency departmen...

A real-world demonstration of machine learning generalizability in the detection of intracranial hemorrhage on head computerized tomography.

Machine learning (ML) holds great promise in transforming healthcare. While published studies have s...

Human inspired fall arrest strategy for humanoid robots based on stiffness ellipsoid optimisation.

Falls are a common risk and impose severe threats to both humans and humanoid robots as a product of...

CXCL1: A new diagnostic biomarker for human tuberculosis discovered using Diversity Outbred mice.

More humans have died of tuberculosis (TB) than any other infectious disease and millions still die ...

Large Vessel Occlusion Prediction in the Emergency Department with National Institutes of Health Stroke Scale Components: A Machine Learning Approach.

OBJECTIVE: To determine the feasibility of using a machine learning algorithm to screen for large ve...

Deep learning approach to assess damage mechanics of bone tissue.

Machine learning methods have the potential to transform imaging techniques and analysis for healthc...

Efficiency of a deep learning-based artificial intelligence diagnostic system in spontaneous intracerebral hemorrhage volume measurement.

BACKGROUND: Accurate measurement of hemorrhage volume is critical for both the prediction of prognos...

A deep learning approach to automate whole-genome prediction of diverse epigenomic modifications in plants.

Epigenetic modifications function in gene transcription, RNA metabolism, and other biological proces...

A Machine Learning Approach in Predicting Mortality Following Emergency General Surgery.

BACKGROUND: There is a significant mortality burden associated with emergency general surgery (EGS) ...

A deep learning algorithm for automatic detection and classification of acute intracranial hemorrhages in head CT scans.

Acute Intracranial hemorrhage (ICH) is a life-threatening disease that requires emergency medical at...

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