Latest AI and machine learning research in emergency medicine for healthcare professionals.
Emerging contaminants such as nanoplastics (NPs) pose significant risks to aquatic ecosystems. However, the key features governing NPs toxicity and the variations in their effects across different trophic levels remain poorly understood. Herein, we integrated machine learning with meta-analysis to comprehensively evaluate NPs toxicity towards aquatic organisms under different conditions, based on ...
Anemia's high global prevalence and socio-economic burden necessitate early diagnosis, yet reliance on invasive blood testing creates significant barriers to diagnosis and treatment. To address this, we developed a deep learning model using the Detection Transformer framework for the rapid, non-invasive assessment of anemia severity in a real-world emergency department setting. Comparing a lip-foc...
BACKGROUND: Delayed union and nonunion remain clinically important complications after tibial and femoral shaft fractures. Although traditional risk f...
Osteoporosis is a skeletal disease that significantly increases fracture risk and imposes a growing public health and economic burden. Notably, hip fr...
BACKGROUND: Annually, stroke affects over 15Â million people globally. Early intervention is critical in the management of stroke. However, the "golden...
Perfluorooctane sulfonate (PFOS), a persistent member of the per- and polyfluoroalkyl substances family, has been increasingly associated with adverse...
To investigate the potential molecular mechanisms underlying aspartame (APM)-induced malignant phenotypic changes in colorectal cancer (CRC). Candidat...
Miniaturization has emerged as a major technological trajectory in robotic surgery, encompassing single-port systems, flexible endoscopic platforms, c...
Artificial intelligence (AI) is reshaping healthcare, and radiology is at the forefront for adoption. Increasing demand for imaging, complex protocols...
INTRODUCTION: The integration of artificial intelligence (AI) into addiction research has expanded rapidly, yet it remains unclear how psychosocial, b...
OBJECTIVE: To compare robotic body weight supported treadmill training (RBWSTT), overground robotic exoskeleton training (ORET), and conventional phys...
STUDY OBJECTIVES: To compare end-of-life predictions as measured by the physician-answered surprise question (SQ), "Would you be surprised if this pat...
UNLABELLED: AI-derived bone mineral density from routine radiographs showed strong agreement with DXA and comparable ability to predict incident fract...
While the biochemical impacts of heavy metals on aquatic organisms are well-documented, quantitative behavioral analyses remain limited. This study in...
AIM: Out-of-hospital cardiac arrest (OHCA) remains a leading cause of death. Although emergency medical dispatchers represent the first link in the Ch...
OBJECTIVES: To evaluate the performance of Chat Generative Pre-Trained Transformer-4 Omni (ChatGPT-4o) in answering multimodal critical care board rev...
BACKGROUND: Emergency department (ED) crowding is a global challenge with adverse effects on patient outcomes and staff well-being. Traditional crowdi...
Liquid crystal monomers (LCMs) are emerging contaminants whose system-level toxicity mechanisms remain poorly understood. Here, we developed a pathway...
OBJECTIVE: To determine whether contemporary large language models can match clinician performance in evaluating the urgency of emergency otolaryngolo...
BACKGROUND: Prognostic assessment in secondary care settings remains challenging and may influence clinical decision-making and follow-up. Artificial ...