Emergency Medicine

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

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Showing 379-399 of 5,216 articles
An assessment of machine learning methods to quantify blood lactate from neutrophils phagocytic activity.

Phagocytosis is a critical component of innate immunity that helps the body defend itself against in...

A systematic review of machine learning-based prognostic models for acute pancreatitis: Towards improving methods and reporting quality.

BACKGROUND: An accurate prognostic tool is essential to aid clinical decision-making (e.g., patient ...

Machine learning using random forest to differentiate between blow and fall situations of head trauma.

Blunt head trauma is a common occurrence in forensic practice. Interpreting the origin of craniocere...

AI-MET: A deep learning-based clinical decision support system for distinguishing multisystem inflammatory syndrome in children from endemic typhus.

The COVID-19 pandemic brought several diagnostic challenges, including the post-infectious sequelae ...

Towards Rapid and Low-Cost Stroke Detection Using SERS and Machine Learning.

Stroke affects approximately 12 million individuals annually, necessitating swift diagnosis to avert...

Prediction of Poisson's ratio for a petroleum engineering application: Machine learning methods.

Static Poisson's ratio (νs) is an essential property used in petroleum calculations, namely fracture...

The Mechanism of Bisphenol S-Induced Atherosclerosis Elucidated Based on Network Toxicology, Molecular Docking, and Machine Learning.

The increasing prevalence of environmental pollutants has raised public concern about their potentia...

Development of a Machine-Learning Algorithm to Identify Cauda Equina Compression on Magnetic Resonance Imaging Scans.

OBJECTIVE: Cauda equina syndrome (CES) poses significant neurological risks if untreated. Diagnosis ...

Impact of deep learning on pediatric elbow fracture detection: a systematic review and meta-analysis.

OBJECTIVES: Pediatric elbow fractures are a common injury among children. Recent advancements in art...

Automated identification of incidental hepatic steatosis on Emergency Department imaging using large language models.

BACKGROUND: Hepatic steatosis is a precursor to more severe liver disease, increasing morbidity and ...

LSTM and ResNet18 for optimized ambulance routing and traffic signal control in emergency situations.

Traffic congestion, particularly in rapidly expanding urban centers, significantly impacts the timel...

Predicting PTSD development with early post-trauma assessments: a proof-of-concept for a concise tree-based classification method.

Approximately 70% of individuals globally experience at least one traumatic event in their lifetime...

Development and validation of interpretable machine learning models for triage patients admitted to the intensive care unit.

OBJECTIVES: Developing and validating interpretable machine learning (ML) models for predicting whet...

Label-efficient sequential model-based weakly supervised intracranial hemorrhage segmentation in low-data non-contrast CT imaging.

BACKGROUND: In clinical settings, intracranial hemorrhages (ICH) are routinely diagnosed using non-c...

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