Latest AI and machine learning research in emergency medicine for healthcare professionals.
BACKGROUND: Traumatic musculoskeletal injuries are a common presentation to emergency care, the first-line investigation often being plain radiography. The interpretation of this imaging frequently falls to less experienced clinicians despite well-established challenges in reporting. This study presents novel data of clinicians' confidence in interpreting trauma radiographs, their perception of AI...
This article presents an analysis of European smart city narratives and how they evolved under the pressure of the COVID-19 pandemic. We start with Joss et al.'s observation that the smart-city discourse is presently in flux, engaged in intensive boundary-work and struggling to gain wider support. We approach this process from the critical perspective of surveillance capitalism, as proposed by Zub...
BACKGROUND: Artificial intelligence (AI) is steadily entering and transforming the health care and Primary Care (PC) domains. AI-based applications as...
How to allocate the existing medical resources reasonably, alleviate hospital congestion and improve the patient experience are problems faced by all ...
At present, urban flood risk analysis and forecasting and early warning mainly use numerical models for simulation and analysis, which are more accura...
Orthopedic surgery remains technically demanding due to the complex anatomical structures and cumbersome surgical procedures. The introduction of imag...
Computer-assisted procedures are becoming increasingly more relevant in orthopedics and trauma surgery. The data situation on these systems has improv...
BACKGROUND: Artificial intelligence (AI) is gaining traction in medicine and surgery. AI-based applications can offer tools to examine high-volume dat...
BACKGROUND AND PURPOSE: Intracranial hemorrhage (ICH) is a common life-threatening condition that must be rapidly diagnosed and treated. However, ther...
One of the major challenges in drug development is having acceptable levels of efficacy and safety throughout all the phases of clinical trials follow...
Robot-assisted partial nephrectomy (RAPN) has traditionally been performed as an inpatient procedure; however, recent studies have suggested the feas...
INTRODUCTION: Patient-operated digital triage systems with AI components are becoming increasingly common. However, previous reviews have found a limi...
BACKGROUND: To develop an end-to-end deep learning method for automated quantitative assessment of pediatric blunt hepatic trauma based on contrast-en...
Flexible sensing devices (FSDs) fabricated using conductive hydrogels have attracted researchers' extensive enthusiasm in recent years due to their ve...
Deep learning algorithms can be used to classify medical images. In distal radius fracture treatment, fracture detection and radiographic assessment o...
The roles of emergency responders are challenging and often physically demanding, so it is essential that their duties are performed safely and effect...
BACKGROUND AND OBJECTIVE: In the process of robotic fracture reduction, there is a risk of unintended collision of broken bones, which is not conduciv...
Fires are one of the main disasters in underground engineering. In order to comprehensively describe and evaluate the risk of underground engineering ...
A flexible needle has emerged as a crucial clinical technique in contemporary medical practices, particularly for minimally invasive interventions. It...
Herein, a robust and reproducible eXplainable Artificial Intelligence (XAI) approach is presented, which allows prediction of developmental toxicity, ...