AIMC Topic: Clinical Competence

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From Cases to Confidence: Developing Diagnostic Reasoning Skills Through Collaborative Learning in Graduate Nursing Education.

Nursing education perspectives
Teaching diagnostic reasoning to graduate nursing students is both essential and challenging, particularly in asynchronous environments where absence of real-time interaction requires innovative strategies to engage students and support the developme...

The Evolving Role of Artificial Intelligence in Plastic Surgery Education: Insights From Program Directors and Residents.

Journal of surgical education
OBJECTIVE: To assess the current state of artificial intelligence (AI) policies, educational resources, and perceptions within U.S. plastic surgery residency programs from the perspectives of program directors (PDs) and residents.

The Year in Graduate Medical Education: Selected Highlights from 2024.

Journal of cardiothoracic and vascular anesthesia
This special article is the fourth in an annual series for the Journal of Cardiothoracic and Vascular Anesthesia that highlights significant literature from the world of graduate medical education that was published over the past year. Some of the ma...

Evaluating Large Language Models on American Board of Anesthesiology-style Anesthesiology Questions: Accuracy, Domain Consistency, and Clinical Implications.

Journal of cardiothoracic and vascular anesthesia
Recent advances in large language models (LLMs) have led to growing interest in their potential applications in medical education and clinical practice. This study evaluated whether five widely used and highly developed LLMs-ChatGPT-4, Gemini, Claude...

The Data-Augmented, Technology-Assisted Medical Decision Making (DATA-MD) Curriculum: A Machine Learning and Artificial Intelligence Curriculum for Clinical Trainees.

Academic medicine : journal of the Association of American Medical Colleges
PROBLEM: Despite the rapidly expanding role of artificial intelligence (AI) and machine learning (ML) in health care, a significant knowledge gap remains among clinicians in their ability to evaluate and use AI and ML tools.

Performance of ChatGPT-4 Omni and Gemini 1.5 Pro on Ophthalmology-Related Questions in the Turkish Medical Specialty Exam.

Turkish journal of ophthalmology
OBJECTIVES: To evaluate the response and interpretative capabilities of two pioneering artificial intelligence (AI)-based large language model (LLM) platforms in addressing ophthalmology-related multiple-choice questions (MCQs) from Turkish Medical S...

Effect of Deep Learning-Based Artificial Intelligence on Radiologists' Performance in Identifying Nigrosome 1 Abnormalities on Susceptibility Map-Weighted Imaging.

Korean journal of radiology
OBJECTIVE: To evaluate the effect of deep learning (DL)-based artificial intelligence (AI) software on the diagnostic performance of radiologists with different experience levels in detecting nigrosome 1 (N1) abnormalities on susceptibility map-weigh...

Evaluating Artificial Intelligence and Traditional Learning Tools for Chest X-Ray Interpretation: A Descriptive Study.

The clinical teacher
BACKGROUND: Chest X-ray (CXR) interpretation is a fundamental yet challenging skill for medical students to master. Traditional resources like Radiopaedia offer extensive content, while newer artificial intelligence (AI) tools, such as Chester, provi...

Surgical skill assessment using an AI-based surgical phase recognition model for laparoscopic cholecystectomy.

Surgical endoscopy
BACKGROUND: Automated surgical skill assessment using artificial intelligence (AI) in laparoscopic cholecystectomy (Lap-C) can be a valuable method for improving the effectiveness of surgical education and enhancing the surgical outcomes of Lap-C. Th...