Latest AI and machine learning research in emergency medicine for healthcare professionals.
The sodium-iodide symporter (NIS, SLC5A5) plays a crucial role in thyroid hormone synthesis. Especially during brain development, correct thyroid signaling is of critical importance. Hence, inhibition of this transporter can lead to neurodevelopmental disorders, such as lowered IQ or autism. In order to uncover environmental chemicals with the potential of causing developmental neurotoxicity (DNT)...
OBJECTIVES: To quantify fetal brain maturation in fetuses with early-onset fetal growth restriction (FGR) by estimating gestational age (GA) based on the appearance of gyrification and individual brain structures from three-dimensional (3D) ultrasound volumes using a deep-learning model trained on optimally developing subjects. The association of altered fetal brain maturation, as a potential mark...
Understanding the behavioral and morphological dynamics of moving model organisms like the zebrafish larvae requires accurate, high-throughput 3D anal...
PURPOSE OF REVIEW: Point-of-care ultrasound (POCUS) has transformed emergency medicine by providing a noninvasive, accessible, repeatable, efficient, ...
As artificial intelligence tools become increasingly integrated into emergency department workflows, healthcare providers face a growing risk of legal...
WHAT WAS THE EDUCATIONAL CHALLENGE?: Resuscitation debriefing requires accurate timeline reconstruction for effective team learning. Standard document...
BACKGROUND: Deep learning models have shown strong potential for automated fracture detection in medical images. However, their robustness under varyi...
This study aims to construct a predictive model for post-thrombectomy hemorrhagic transformation (HT) by integrating hemodynamic features derived from...
Coagulation dysfunction, a common hematologic disorder with unclear pathogenesis, is influenced by environmental factors. Sodium dehydroacetate (SDA),...
BACKGROUND: Massive transfusion protocols are established in-hospital practices for managing haemorrhagic shock, yet critical bleeding accounts for up...
PURPOSE: To present a comprehensive framework for integrating oculomics to assess ocular and systemic health into coordinated health care delivery mod...
BACKGROUND: This study aimed to demonstrate the feasibility of using computer vision (CV) to unobtrusively extract body motion metrics from videos of ...
UNLABELLED: Opportunistic analysis of chest radiographs with deep learning detects osteoporosis cost-effectively in women aged ≥ 50 years in Singapore...
BACKGROUND: Spinal surgery is a highly complex field increasingly shaped by digital innovation. Artificial intelligence (AI) and machine learning (ML)...
The development of infrared engineering technologies for extreme environments remains a formidable challenge due to the inherent trade-offs among opti...
Neonatal prematurity leads to considerable morbidity and mortality, partly because of acquired conditions such as bronchopulmonary dysplasia (BPD), in...
Diabetic retinopathy (DR) is one of the most common complications of diabetes, and timely detection of retinal hemorrhages is essential for preventing...
BACKGROUND AND AIMS: The accurate and timely diagnosis of ileus versus volvulus is essential in emergency care, as treatment choices directly influenc...
BACKGROUND: E-medicine use has surged, and health systems are exploring large language models (LLMs) for message triage. However, it is still unknown ...
INTRODUCTION: Artificial intelligence (AI) is increasingly embedded in healthcare, with expanding applications in emergency medicine (EM). OBJECTIVE: ...