RATIONALE AND OBJECTIVES: To evaluate the performance of various multimodal large language models (LLMs) in the Japanese Diagnostic Radiology Board Examinations (JDRBE) both with and without images.
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...
PURPOSE: With the popularization of ChatGPT (Open AI, San Francisco, California, United States) in recent months, understanding the potential of artificial intelligence (AI) chatbots in a medical context is important. Our study aims to evaluate Googl...
RATIONALE AND OBJECTIVES: The objective of this study was to evaluate the effectiveness of a pilot artificial intelligence (AI) certificate program in aiding radiology trainees to develop an understanding of the evolving role and application of artif...
RATIONALE AND OBJECTIVES: The American Registry of Radiologic Technologists (ARRT) leads the certification process with an exam comprising 200 multiple-choice questions. This study aims to evaluate ChatGPT-4's performance in responding to practice qu...
Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
39617127
BACKGROUND: Previous studies evaluated the ability of large language models (LLMs) in medical disciplines; however, few have focused on image analysis, and none specifically on cardiovascular imaging or nuclear cardiology. This study assesses four LL...
BACKGROUND: Large language models (LLMs) have dominated public interest due to their apparent capability to accurately replicate learned knowledge in narrative text. However, there is a lack of clarity about the accuracy and capability standards of L...
This study uses the Oracle SQL certification exam questions to explore the design of automatic classifiers for exam questions containing code snippets. SQL's question classification assigns a class label in the exam topics to a question. With this cl...