Emergency Medicine

Application of machine learning in the study of development, behavior, nerve, and genotoxicity of zebrafish.

Machine learning (ML) as a novel model-based approach has been used in studying aquatic toxicology i...

Statistical machine learning models for prediction of China's maritime emergency patients in dynamic: ARIMA model, SARIMA model, and dynamic Bayesian network model.

INTRODUCTION: Rescuing individuals at sea is a pressing global public health issue, garnering substa...

Identification and validation of cuproptosis-related genes in acetaminophen-induced liver injury using bioinformatics analysis and machine learning.

BACKGROUND: Acetaminophen (APAP) is commonly used as an antipyretic analgesic. However, acetaminophe...

A Comparative Study of a Nomogram and Machine Learning Models in Predicting Early Hematoma Expansion in Hypertensive Intracerebral Hemorrhage.

RATIONALE AND OBJECTIVES: Early identification for hematoma expansion can help improve patient outco...

Advancing toxicity studies of per- and poly-fluoroalkyl substances (pfass) through machine learning: Models, mechanisms, and future directions.

Perfluorinated and perfluoroalkyl substances (PFASs), encompassing a vast array of isomeric chemical...

The potential role for artificial intelligence in fracture risk prediction.

Osteoporotic fractures are a major health challenge in older adults. Despite the availability of saf...

The premise, promise, and perils of artificial intelligence in critical care cardiology.

Artificial intelligence (AI) is an emerging technology with numerous healthcare applications. AI cou...

Detecting Mandible Fractures in CBCT Scans Using a 3-Stage Neural Network.

After nasal bone fractures, fractures of the mandible are the most frequently encountered injuries o...

Inter-Rater and Intra-Rater Agreement in Scoring Severity of Rodent Cardiomyopathy and Relation to Artificial Intelligence-Based Scoring.

We previously developed a computer-assisted image analysis algorithm to detect and quantify the micr...

Assessment of Deep Learning-Based Triage Application for Acute Ischemic Stroke on Brain MRI in the ER.

RATIONALE AND OBJECTIVES: To assess a deep learning application (DLA) for acute ischemic stroke (AIS...

Prediction of mortality among severely injured trauma patients A comparison between TRISS and machine learning-based predictive models.

BACKGROUND: Given the huge impact of trauma on hospital systems around the world, several attempts h...

Cardiac arrest and medical technological innovations in the next decade: How about artificial intelligence-assisted tailored cardiopulmonary resuscitation?

Prospective Evaluation of Artificial Intelligence Triage of Incidental Pulmonary Emboli on Contrast-Enhanced CT Examinations of the Chest or Abdomen.

Artificial intelligence (AI) algorithms improved detection of incidental pulmonary embolism (IPE) o...

Machine learning for the prediction of in-hospital mortality in patients with spontaneous intracerebral hemorrhage in intensive care unit.

This study aimed to develop a machine learning (ML)-based tool for early and accurate prediction of ...

Prediction of developmental toxic effects of fine particulate matter (PM) water-soluble components via machine learning through observation of PM from diverse urban areas.

The global health implications of fine particulate matter (PM) underscore the imperative need for re...

Health consumers' ethical concerns towards artificial intelligence in Australian emergency departments.

OBJECTIVES: To investigate health consumers' ethical concerns towards the use of artificial intellig...

Prediction of post-delivery hemoglobin levels with machine learning algorithms.

Predicting postpartum hemorrhage (PPH) before delivery is crucial for enhancing patient outcomes, en...

Deep learning survival model predicts outcome after intracerebral hemorrhage from initial CT scan.

BACKGROUND: Predicting functional impairment after intracerebral hemorrhage (ICH) provides valuable ...

Assessing the effectiveness of artificial intelligence (AI) in prioritising CT head interpretation: study protocol for a stepped-wedge cluster randomised trial (ACCEPT-AI).

INTRODUCTION: Diagnostic imaging is vital in emergency departments (EDs). Accessibility and reportin...

Patient stratification based on the risk of severe illness in emergency departments through collaborative machine learning models.

OBJECTIVES: Emergency department (ED) overcrowding presents a global challenge that inhibits prompt ...

Estimation of invasive coronary perfusion pressure using electrocardiogram and Photoplethysmography in a porcine model of cardiac arrest.

BACKGROUND: Coronary perfusion pressure (CPP) indicates spontaneous return of circulation and is rec...