With the public release of ChatGPT before the 2024 dermatology residency application cycle, applicants gained access to an advanced language model capable of generating or enhancing personal statements. This study examines trends in artificial intell...
PURPOSE: To investigate whether cataract surgical skill performance metrics automatically generated by artificial intelligence (AI) models can differentiate between trainee and faculty surgeons and the correlation between AI metrics and expert-rated ...
Medical interns are at high risk of acquiring Hepatitis B Virus (HBV) infection during their training. HBV vaccination is the most effective measure to reduce the global incidence of HBV. The duration of protection after HBV vaccination is still cont...
The Journal of the American Academy of Orthopaedic Surgeons
40101179
PURPOSE: Artificial intelligence (AI) has been increasingly studied within medical education and clinical practice. At present, it remains uncertain if AI is being used to write personal statements (PSs) for orthopaedic surgery residency applications...
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
40337975
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...
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...
BACKGROUND: The integration of artificial intelligence (AI) in medical education assessment remains largely unexplored, particularly in specialty-specific evaluations during clinical rotations. Traditional question development methods are time-intens...
BACKGROUND: As health care moves to a more digital environment, there is a growing need to train future family doctors on the clinical uses of artificial intelligence (AI). However, family medicine training in AI has often been inconsistent or lackin...
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 ...