Emergency Medicine

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

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Showing 484-504 of 5,218 articles
Revolutionizing Health Care: The Transformative Impact of Large Language Models in Medicine.

Large language models (LLMs) are rapidly advancing medical artificial intelligence, offering revolut...

Seismic anisotropy prediction using ML methods: A case study on an offshore carbonate oilfield.

Estimating seismic anisotropy parameters, such as Thomson's parameters, is crucial for investigating...

Melanoma Breslow Thickness Classification Using Ensemble-Based Knowledge Distillation With Semi-Supervised Convolutional Neural Networks.

Melanoma is considered a global public health challenge and is responsible for more than 90% deaths ...

Countering AI-powered disinformation through national regulation: learning from the case of Ukraine.

Advances in the use of AI have led to the emergence of a greater variety of forms disinformation can...

ICH-PRNet: a cross-modal intracerebral haemorrhage prognostic prediction method using joint-attention interaction mechanism.

Accurately predicting intracerebral hemorrhage (ICH) prognosis is a critical and indispensable step ...

Predicting and Ranking Diabetic Ketoacidosis Risk Among Youth with Type 1 Diabetes with a Clinic-to-Clinic Transferrable Machine Learning Model.

To use electronic health record (EHR) data to develop a scalable and transferrable model to predict...

Clinicians' perspectives on the use of artificial intelligence to triage MRI brain scans.

Artificial intelligence (AI) tools can triage radiology scans to streamline the patient pathway and ...

Predicting emergency department admissions using a machine-learning algorithm: a proof of concept with retrospective study.

INTRODUCTION: Overcrowding in emergency departments (ED) is a major public health issue, leading to ...

Interpretable machine learning for predicting sepsis risk in emergency triage patients.

The study aimed to develop and validate a sepsis prediction model using structured electronic medica...

Managing emergency crises using secure information through educational awareness: COVID-19 case study.

Social networks are increasingly taking over daily life, creating a volume of unsecured data and mak...

From Spectra to Signatures: Detecting Fentanyl in Human Nails with ATR-FTIR and Machine Learning.

Human nails have recently become a sample of interest for toxicological purposes. Multiple studies h...

Novel transfer learning based bone fracture detection using radiographic images.

A bone fracture is a medical condition characterized by a partial or complete break in the continuit...

Utilizing integrated bioinformatics and machine learning approaches to elucidate biomarkers linking sepsis to purine metabolism-associated genes.

Sepsis, characterized as a systemic inflammatory response triggered by pathogen invasion, represents...

Varying pixel resolution significantly improves deep learning-based carotid plaque histology segmentation.

Carotid plaques-the buildup of cholesterol, calcium, cellular debris, and fibrous tissues in carotid...

International multicenter validation of AI-driven ultrasound detection of ovarian cancer.

Ovarian lesions are common and often incidentally detected. A critical shortage of expert ultrasound...

Prediction of sepsis among patients with major trauma using artificial intelligence: a multicenter validated cohort study.

BACKGROUND: Sepsis remains a significant challenge in patients with major trauma in the ICU. Early d...

Forecasting Pediatric Trauma Volumes: Insights From a Retrospective Study Using Machine Learning.

INTRODUCTION: Rising pediatric firearm-related fatalities in the United States strain Trauma Centers...

Human intention recognition for trauma resuscitation: An interpretable deep learning approach for medical process data.

OBJECTIVE: Trauma resuscitation is the initial evaluation and management of injured patients in the ...

Leveraging Machine Learning to Identify Subgroups of Misclassified Patients in the Emergency Department: Multicenter Proof-of-Concept Study.

BACKGROUND: Hospitals use triage systems to prioritize the needs of patients within available resour...

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