Emergency Medicine

Artificial intelligence versus surgeon gestalt in predicting risk of emergency general surgery.

BACKGROUND: Artificial intelligence (AI) risk prediction algorithms such as the smartphone-available...

CT Angiography Radiomics Combining Traditional Risk Factors to Predict Brain Arteriovenous Malformation Rupture: a Machine Learning, Multicenter Study.

This study aimed to develop a machine learning model for predicting brain arteriovenous malformation...

Prediction of Human Organ Toxicity via Artificial Intelligence Methods.

Unpredicted human organ level toxicity remains one of the major reasons for drug clinical failure. T...

Deep Learning for the Assessment of Facial Nerve Palsy: Opportunities and Challenges.

Automated evaluation of facial palsy using machine learning offers a promising solution to the limit...

Crowd-Sourced Deep Learning for Intracranial Hemorrhage Identification: Wisdom of Crowds or Laissez-Faire.

BACKGROUND AND PURPOSE: Researchers and clinical radiology practices are increasingly faced with the...

Using Deep Learning to Detect the Presence and Location of Hemoperitoneum on the Focused Assessment with Sonography in Trauma (FAST) Examination in Adults.

Abdominal ultrasonography has become an integral component of the evaluation of trauma patients. Int...

Probabilistic real-time natural gas jet fire consequence modeling of offshore platforms by hybrid deep learning approach.

Natural gas jet fire induced by igniting blowouts has the potential to cause critical structure dama...

The evolution and development of a robotic acute care surgery program.

BACKGROUND: Acute care surgeons perform more than 850,000 operations annually on emergency general s...

Explainable COVID-19 Detection Based on Chest X-rays Using an End-to-End RegNet Architecture.

COVID-19,which is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is one...

[Application of artificial intelligence systems in the emergency room : Do the communication patterns give indications for possible starting points? An observational study].

BACKGROUND: High expectations are currently attached to the application of artificial intelligence (...

Erroneous electrocardiographic interpretations and its clinical implications.

INTRODUCTION: The advancement of artificial intelligence (AI) has aided clinicians in the interpreta...

Systematic Review of Artificial Intelligence for Abnormality Detection in High-volume Neuroimaging and Subgroup Meta-analysis for Intracranial Hemorrhage Detection.

PURPOSE: Most studies evaluating artificial intelligence (AI) models that detect abnormalities in ne...

Development of a Deep Learning Model for Retinal Hemorrhage Detection on Head Computed Tomography in Young Children.

IMPORTANCE: Abusive head trauma (AHT) in children is often missed in medical encounters, and retinal...

Emergency surgery in the era of artificial intelligence: ChatGPT could be the doctor's right-hand man.

Deep learning in optical coherence tomography: Where are the gaps?

Optical coherence tomography (OCT) is a non-invasive optical imaging modality, which provides rapid,...

The application of artificial intelligence to accelerate G protein-coupled receptor drug discovery.

The application of artificial intelligence (AI) approaches to drug discovery for G protein-coupled r...

Advancing Computational Toxicology by Interpretable Machine Learning.

Chemical toxicity evaluations for drugs, consumer products, and environmental chemicals have a criti...

Reconstructive Allograft Preparation for Long Bone Intercalary Segments After Tumor Resections: Toronto Sarcoma Protocol.

BACKGROUND: The Reconstructive Allograft Preparation by Toronto Sarcoma (RAPTORS) protocol is reliab...

Using Natural Language Processing to Predict Fatal Drug Overdose From Autopsy Narrative Text: Algorithm Development and Validation Study.

BACKGROUND: Fatal drug overdose surveillance informs prevention but is often delayed because of auto...

Real-World Performance of Large Vessel Occlusion Artificial Intelligence-Based Computer-Aided Triage and Notification Algorithms-What the Stroke Team Needs to Know.

PURPOSE: To evaluate the real-world performance of two FDA-approved artificial intelligence (AI)-bas...

Neurosurgical skills analysis by machine learning models: systematic review.

Machine learning (ML) models are being actively used in modern medicine, including neurosurgery. Thi...