Emergency Medicine

Optimal mean arterial pressure for favorable neurological outcomes in patients after cardiac arrest.

BACKGROUND: Optimal mean arterial pressure (MAP) range after cardiac arrest remains uncertain. This ...

Retrospective study of onychomycosis patients treated with ciclopirox 8% HPCH and oral antifungals applying artificial intelligence to electronic health records.

We conducted a multicenter retrospective analysis of 408 patients diagnosed with onychomycosis who a...

Predicting distal tibia fracture type using demographic, vehicle, and crash factors via a random forest classification algorithm.

OBJECTIVE: Distal tibia fractures occur in approximately 4% of police-reported crashes where at leas...

Trauma-predictive brain network connectivity adaptively responds to mild acute stress.

Past traumatic experiences shape neural responses to future stress, but the mechanisms underlying th...

AI search, physician removal: Bronchoscopy robot bridges collaboration in foreign body aspiration.

Bronchial foreign body aspiration is a life-threatening condition with a high incidence across diver...

Association between long-term exposure of polystyrene microplastics and exacerbation of seizure symptoms: Evidence from multiple approaches.

Microplastics are tiny plastic particles originating from both commercial product manufacturing and ...

Machine learning and network toxicology reveal arsenic as a key driver of non-carcinogenic health risks from heavy metal residues in Chinese medicinal plants.

Heavy metal (HM) residues in Chinese medicinal plants (CMPs) threaten their quality and human health...

Predicting Emergency Severity Index (ESI) level, hospital admission, and admitting ward in an emergency department using data-driven machine learning.

INTRODUCTION: Emergency departments (EDs) are critical for ensuring timely patient care, especially ...

Emergency medical services providers' perspectives on the use of artificial intelligence in prehospital identification of stroke- a qualitative study in Norway and Sweden.

BACKGROUND: Stroke is a large and increasing health challenge, leading to acquired physical disabili...

Non-Invasive Bedside Approaches for Assessing Microvascular Dysfunction.

Microvascular dysfunction is implicated in a range of acute and chronic conditions, ranging from car...

The evolution of research in orthopedic robotic surgery: global trends and future directions.

Robotic surgery enhances precision in orthopedic and trauma procedures like joint replacements and b...

Self-Assessment of acute rib fracture detection system from chest X-ray: Preliminary study for early radiological diagnosis.

ObjectiveDetecting and accurately diagnosing rib fractures in chest radiographs is a challenging and...

Hyperparameter tuned deep learning-driven medical image analysis for intracranial hemorrhage detection.

Intracranial haemorrhage (ICH) is a crucial medical emergency that entails prompt assessment and man...

Toxicological Mechanisms: Moving Forward with Artificial IntelligenceToxicological Mechanisms: Moving Forward with Artificial Intelligence.

Comments on "deep learning for kidney trauma detection: CT image algorithm performance and external validation. - experimental study".

Systematic review of commercial artificial intelligence tools for the detection and volume quantification in intracerebral hemorrhage.

OBJECTIVES: This systematic review evaluates commercial imaging-based artificial intelligence (AI) s...

EXPEDITION: an Exploratory deep learning method to quantitatively predict hematoma progression after intracerebral hemorrhage.

OBJECTS: This study aims to develop an Exploratory deep learning method to quantitatively predict he...

Agentic AI in radiology: Emerging Potential and Unresolved Challenges.

This commentary introduces agentic artificial intelligence (AI) as an emerging paradigm in radiology...

Predicting Traumatic Brain Injury Post-Trauma Using Temporal Attention on Sleep-Wake Data.

BACKGROUND: Traumatic Brain Injury (TBI) is a major public health concern, and accurate classificati...

Analyzing pediatric forearm X-rays for fracture analysis using machine learning.

PURPOSE: Forearm fractures constitute a significant proportion of emergency department presentations...

A Dynamic Machine Learning Model to Predict Angiographic Vasospasm After Aneurysmal Subarachnoid Hemorrhage.

BACKGROUND AND OBJECTIVES: The goal of this study was to develop a highly precise, dynamic machine l...