Emergency Medicine

Prediction of contrast-associated acute kidney injury with machine-learning in patients undergoing contrast-enhanced computed tomography in emergency department.

Radiocontrast media is a major cause of nephrotoxic acute kidney injury(AKI). Contrast-enhanced CT(CE-CT) is commonly performed in emergency departments(ED). Predicting individualized risks of contrast-associated AKI(CA-AKI) in ED patients is challenging due to a narrow time window and rapid patient turnover. We aimed to develop machine-learning(ML) models to predict CA-AKI in ED patients. Adult E...

Machine Learning-Based Prediction of Postoperative Pneumonia Among Super-Aged Patients With Hip Fracture.

BACKGROUND: Hip fractures have become a significant health concern, particularly among super-aged patients, who were at a high risk of postoperative pneumonia due to their frailty and the presence of multiple comorbidities. This study aims to establish and validate a model to predict postoperative pneumonia among super-aged patients with hip fracture.

Using explainable machine learning to investigate the relationship between childhood maltreatment, positive psychological traits, and CPTSD symptoms.

The functional impairment resulting from CPTSD symptoms is enduring and far-reaching. Existing research has found that CPTSD symptoms are closely ass...

Using Machine Learning to Improve Readmission Risk in Surgical Patients in South Africa.

Unplanned readmission within 30 days is a major challenge both globally and in South Africa. The aim of this study was to develop a machine learning m...

Machine learning-based optimal design of fibrillar adhesives.

Fibrillar adhesion, observed in animals like beetles, spiders and geckos, relies on nanoscopic or microscopic fibrils to enhance surface adhesion via ...

Deep-learning tool for early identification of non-traumatic intracranial hemorrhage etiology and application in clinical diagnostics based on computed tomography (CT) scans.

BACKGROUND: To develop an artificial intelligence system that can accurately identify acute non-traumatic intracranial hemorrhage (ICH) etiology (aneu...

Development and evaluation of a multivariable prediction model for overall survival in advanced stage pulmonary carcinoid using machine learning.

BACKGROUND: Evidence is limited on whether patients with advanced pulmonary carcinoid (APC) benefit from comprehensive pulmonary resection (CPR), chem...

Machine Learning Predicts Bleeding Risk in Atrial Fibrillation Patients on Direct Oral Anticoagulant.

Predicting major bleeding in nonvalvular atrial fibrillation (AF) patients on direct oral anticoagulants (DOACs) is crucial for personalized care. Alt...

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 infection, foreign particles, and cellular debris. I...

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 craniocerebral injuries can be a challenging process, partic...

Development of a deep neural network model based on high throughput screening data for predicting synergistic estrogenic activity of binary mixtures for consumer products.

A paradigm of chemical risk assessment is continuously extending from focusing on 'single substances' to more comprehensive approaches that examines t...

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 multisystem inflammatory syndrome in children (MIS...

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

Stroke affects approximately 12 million individuals annually, necessitating swift diagnosis to avert fatal outcomes. Current hospital imaging protocol...

Performance of machine learning models in predicting difficult laryngoscopy in the emergency department: a single-centre retrospective study comparing with conventional regression method.

BACKGROUND: Emergency endotracheal intubation is a critical skill for managing airway emergencies in the emergency department (ED). Accurate predictio...

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 pressure (FP). The νs is often determined in the ...

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 potential role in diseases such as atherosclerosis (AS). E...

Advancing exposure science through artificial intelligence: Neural ordinary differential equations for predicting blood concentrations of volatile organic compounds.

Volatile organic compounds (VOCs) are a significant concern for human health and environmental safety, requiring accurate models to predict their conc...

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 artificial intelligence (AI), particularly deep learn...

Assessment of large language models in medical quizzes for clinical chemistry and laboratory management: implications and applications for healthcare artificial intelligence.

Large language models (LLMs) have demonstrated high performance across various fields due to their ability to understand, generate, and manipulate hum...

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 mortality risks. In the Emergency Department, rout...