… Conclusions and Relevance In a representative sample of emergency department chest
radiographs, results suggest that the generative AI model produced reports of similar clinical …

… a computational model by artificial intelligence (AI) methodologies … clinical variables. A
model to predict hospital admission was developed using neural networks and machine learning …

… years of clinical experience, and 3 emergency physicians with 5 years of clinical experience)…
the AI-based CDSS deployed on the internet with clinical vignettes of model cases, and (3) …

… Artificial Intelligence Applications in Medical Imaging as Applied to Common Cancers. Artificial
intelligence … to 3 broad categories of image-based clinical tasks in oncology: 1) detection …

… challenges that influence its clinical adoption. This scoping review summarizes the current
literature exploring the barriers and facilitators of the clinical implementation of AI in the ED. …

… digital triage but also from the patients’ clinical condition. Following this process, technology
… Moreover, it is important to comprehend that using artificial intelligence based techniques …

Background: During the coronavirus disease 2019 (COVID-19) pandemic, calculation of the
number of emergency department (ED) beds required for patients with vs. without suspected …

… Emergency physician-performed FoCUS can identify clinical … clinical questions of a FoCUS
examination. Many of these handheld devices are beginning to integrate artificial intelligence …

… responsibility will not be so much to extract information from images and histology but to
manage the information extracted by artificial intelligence in the clinical context of the patient. …

… Real-time interactive artificial intelligence of things-based prediction for adverse outcomes
in adult patients with pneumonia in the emergency department. Acad Emerg Med. 2021;28:…