Latest AI and machine learning research in emergency medicine for healthcare professionals.
OBJECTIVES: To model the occurrence of adverse events (AEs) among Veterans prescribed nonsteroidal anti-inflammatory drugs (NSAIDs) during emergency department and urgent care encounters within the Veterans Health Administration (VHA) care setting. NSAIDs can increase the risk for gastrointestinal, renal, and cardiovascular AEs, particularly in older adults, patients with chronic kidney disease (C...
BACKGROUND AND AIMS: Artificial intelligence (AI) is rapidly transforming healthcare and has increasing relevance for physical therapy practice. This review aims to examine how AI can be integrated across the continuum of care within the Physical Therapy Patient and Client Management Model. METHODS: This narrative review synthesizes current literature and emerging applications of AI in rehabilitat...
Children with medical complexity (CMC) are defined by the presence of significant chronic health problems that affect multiple organ systems, often re...
Artificial intelligence (AI) is poised to transform diagnostic radiology, yet data on its adoption and the perspectives of radiologists in the Middle ...
PURPOSE: This study aimed to evaluate the potential of amino-acid profiles to predict disease progression in patients with Crimean-Congo Hemorrhagic F...
BACKGROUND: Emergency department triage is commonly conceptualised as a standardised classification of patient urgency based on vital signs and presen...
BACKGROUND: This study aimed to evaluate the accuracy and reliability of the responses provided by the artificial intelligence applications (chatbots)...
This study comparatively evaluated accuracy and response stability of artificial intelligence (AI)-models in answering diagnostic, therapeutic and pro...
Pathological microenvironments linked to aging, trauma, malignancies, and metabolic disorders significantly hinder bone fractures and frequently resul...
Craniomaxillofacial deformities are primarily caused by congenital anomalies, trauma, or postoperative defects following tumor resection, involving bo...
BACKGROUND: Large language models (LLMs) have shown potential in medical text generation. Senior physician ward round records are critical documents w...
BACKGROUND: Hip fractures are a major global health issue with high mortality and morbidity, especially in older adults. One-year mortality post-surge...
Interstitial lung diseases (ILDs) require early recognition and longitudinal assessment, yet repeated high-resolution computed tomography (HRCT) is of...
Deoxynivalenol (DON) has been reported to exhibit skin toxicity and carcinogenic potential; however, its effects on melanoma remain unclear. We integr...
Bisphenol A (BPA), a ubiquitous environmental endocrine-disrupting chemical extensively used in plastic products, has been increasingly recognized for...
The misuse of benzodiazepines (BZDs) and Z-drugs poses significant global public health challenges. This study maps the scientific evolution and parad...
Machine learning models, especially vision transformers in the domain of medical images, are highly prone to data poisoning attacks, in which a small ...
INTRODUCTION: Although large language models (LLMs) like ChatGPT are increasingly used in clinical reasoning, their reliability in procedural decision...
AIMS: To quantify the heterogeneity of treatment effects of higher versus standard MAP targets on 28-day mortality, to identify distinct clinical phen...