Journal of the American Board of Family Medicine : JABFM
38740475
BACKGROUND: The potential for machine learning (ML) to enhance the efficiency of medical specialty boards has not been explored. We applied unsupervised ML to identify archetypes among American Board of Family Medicine (ABFM) Diplomates regarding the...
PURPOSE: Artificial Intelligence (AI), and specifically ChatGPT, has shown potential in healthcare, yet its performance in specialized medical examinations such as the Orthopaedic Surgery In-Training Examination and European Board Hand Surgery diplom...
BACKGROUND: Over the past decade, artificial intelligence (AI) has expanded significantly with increased adoption across various industries, including medicine. Recently, AI-based large language models such as Generative Pretrained Transformer-3 (GPT...
Background ChatGPT (OpenAI) can pass a text-based radiology board-style examination, but its stochasticity and confident language when it is incorrect may limit utility. Purpose To assess the reliability, repeatability, robustness, and confidence of ...
BACKGROUND: Artificial intelligence models such as ChatGPT (Open AI) have performed well on the exams of various medical and surgical fields. It is not yet known how ChatGPT performs on similar metabolic and bariatric surgery (MBS) questions.