In the coming years, artificial intelligence (AI) and machine learning will likely give rise to profound changes in the field of emergency medicine, and medicine more broadly. This article discusses these anticipated changes in terms of 3 overlapping...
Academic emergency medicine : official journal of the Society for Academic Emergency Medicine
May 16, 2024
OBJECTIVES: Natural language processing (NLP) represents one of the adjunct technologies within artificial intelligence and machine learning, creating structure out of unstructured data. This study aims to assess the performance of employing NLP to i...
BACKGROUND: The utilization of AI language models in education and academia is currently a subject of research, and applications in clinical settings are also being tested. Studies conducted by various research groups have demonstrated that language ...
BACKGROUND: Tools to increase the turnaround speed and accuracy of imaging reports could positively influence ED logistics. The Caire ICH is an artificial intelligence (AI) software developed for ED physicians to recognise intracranial haemorrhages (...
STUDY OBJECTIVE: The workload of clinical documentation contributes to health care costs and professional burnout. The advent of generative artificial intelligence language models presents a promising solution. The perspective of clinicians may contr...
Medical imaging-based triage is a critical tool for emergency medicine in both civilian and military settings. Ultrasound imaging can be used to rapidly identify free fluid in abdominal and thoracic cavities which could necessitate immediate surgical...
Academic medicine : journal of the Association of American Medical Colleges
Jan 12, 2024
PURPOSE: Learner development and promotion rely heavily on narrative assessment comments, but narrative assessment quality is rarely evaluated in medical education. Educators have developed tools such as the Quality of Assessment for Learning (QuAL) ...
OBJECTIVES: We aimed to develop a computer-aided detection (CAD) system to localize and detect the malposition of endotracheal tubes (ETTs) on portable supine chest radiographs (CXRs).
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