BACKGROUND: Objective measures and large datasets are needed to determine aspects of the Clinical Learning Environment (CLE) impacting the essential skill of clinical reasoning documentation. Artificial Intelligence (AI) offers a solution. Here, the ...
OBJECTIVE: Generative Artificial Intelligence (GAI) interfaces have rapidly integrated into various societal domains. Widespread accessibility of GAI for drafting personal statements poses challenges for evaluators to gauge writing ability and person...
OBJECTIVE: Prior work has demonstrated that AI access can help residents more accurately detect pediatric fractures. We wished to evaluate the effectiveness of an unsupervised AI-based training module as a pediatric fracture detection educational too...
International journal of medical informatics
Apr 4, 2025
STUDY PURPOSE: To assess the application of these two large language models (LLMs) for surgical resident examinations and to compare the performance of these LLMs with that of human residents.
INTRODUCTION: Feedback is at the core of competency-based medical education. Learner perceptions of the evaluation process influence how feedback is utilized. Systems emphasize a fixed mindset, prioritizing evaluation over growth. Embracing growth mi...
Large-language models (LLMs) have shown the capability to effectively answer medical board examination questions. However, their ability to answer imagebased questions has not been examined. This study sought to evaluate the performance of two LLMs (...
Acta orthopaedica et traumatologica turcica
Mar 17, 2025
OBJECTIVE: The aim of this study was to evaluate and compare the performance of the artificial intelligence (AI) models ChatGPT-3.5, ChatGPT-4, and Gemini on the Turkish Specialization Training and Development Examination (UEGS) to determine their ut...
BACKGROUND: To investigate the perspectives and expectations of faculty radiologists, residents, and medical students regarding the integration of artificial intelligence (AI) in radiology education, a survey was conducted to collect their opinions a...
RATIONALE AND OBJECTIVES: Assess the feasibility of using a large language model (LLM) to identify valuable radiology teaching cases through report discrepancy detection.
BACKGROUND: The purpose of this study was to evaluate the performance of widely used artificial intelligence (AI) chatbots in answering prosthodontics questions from the Dentistry Specialization Residency Examination (DSRE).
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