AIMC Topic: Emergency Medicine

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Quantifying Emergency Medicine Residency Learning Curves Using Natural Language Processing: Retrospective Cohort Study.

JMIR medical education
BACKGROUND: The optimal duration of emergency medicine (EM) residency training remains a subject of national debate, with the Accreditation Council for Graduate Medical Education considering standardizing all programs to 4 years. However, empirical d...

Evaluating the impact of AI assistance on decision-making in emergency doctors interpreting chest X-rays: a multi-reader multi-case study.

Emergency medicine journal : EMJ
BACKGROUND: Artificial intelligence (AI) tools could assist emergency doctors interpreting chest X-rays to inform urgent care. However, the impact of AI assistance on clinical decision-making, a precursor to enhanced care and patient outcomes, remain...

Can AI match emergency physicians in managing common emergency cases? A comparative performance evaluation.

BMC emergency medicine
BACKGROUND: Large language models (LLMs) such as ChatGPT are increasingly explored for clinical decision support. However, their performance in high-stakes emergency scenarios remains underexamined. This study aimed to evaluate ChatGPT's diagnostic a...

Clinical Performance and Communication Skills of ChatGPT Versus Physicians in Emergency Medicine: Simulated Patient Study.

JMIR medical informatics
BACKGROUND: Emergency medicine can benefit from artificial intelligence (AI) due to its unique challenges, such as high patient volume and the need for urgent interventions. However, it remains difficult to assess the applicability of AI systems to r...

Task-specific versus general-purpose AI models in ECG analysis: A comparative study with emergency medicine specialists.

The American journal of emergency medicine
PURPOSE: To evaluate and compare the diagnostic accuracy of three Artificial intelligence (AI) models-GPT-4o, Canva-GPT, and ECG Reader-GPT-against emergency medicine specialists (EMSs) in electrocardiogram (ECG) interpretation using a standardized a...

AI-Assisted Blood Gas Interpretation: A Comparative Study With an Emergency Physician.

The American journal of emergency medicine
BACKGROUND: Blood gas interpretation is critical in emergency settings. Large language models like ChatGPT are increasingly used in clinical contexts, but their accuracy in interpreting arterial blood gases (ABGs) requires further validation.

AI versus human-generated multiple-choice questions for medical education: a cohort study in a high-stakes examination.

BMC medical education
BACKGROUND: The creation of high-quality multiple-choice questions (MCQs) is essential for medical education assessments but is resource-intensive and time-consuming when done by human experts. Large language models (LLMs) like ChatGPT-4o offer a pro...

Establishing methodological standards for the development of artificial intelligence-based Clinical Decision Support in emergency medicine.

CJEM
OBJECTIVE: Artificial intelligence (AI) offers opportunities for managing the complexities of clinical care in the emergency department (ED), and Clinical Decision Support has been identified as a priority application. However, there is a lack of pub...

The role of artificial intelligence in gynecologic and obstetric emergencies.

European journal of obstetrics, gynecology, and reproductive biology
OBJECTIVE: To investigate the potential of artificial intelligence (AI) in emergency medicine, focusing on its utility in triaging and managing acute gynecologic and obstetric emergencies.

FDA-reviewed artificial intelligence-enabled products applicable to emergency medicine.

The American journal of emergency medicine
OBJECTIVE: To identify and assess artificial intelligence (AI)-enabled products reviewed by the U.S. Food and Drug Administration (FDA) that are potentially applicable to emergency medicine (EM).