Introducing AnatomyGPT: A customized artificial intelligence application for anatomical sciences education

Bradley R Collins; Erik W Black; Kyle E Rarey

doi:10.1002/ca.24178

Introducing AnatomyGPT: A customized artificial intelligence application for anatomical sciences education

Clin Anat. 2024 May 9. doi: 10.1002/ca.24178. Online ahead of print.

Authors

Bradley R Collins¹, Erik W Black², Kyle E Rarey¹

Affiliations

¹ Department of Anatomy and Cell Biology, University of Florida College of Medicine, Gainesville, Florida, USA.
² College of Nursing, University of Florida, Gainesville, Florida, USA.

PMID: 38721869
DOI: 10.1002/ca.24178

Abstract

Artificial intelligence (AI) technologies are poised to become an increasingly important part of education in the anatomical sciences. OpenAI has also introduced generative pretrained transformers (GPTs), which are customizable versions of the standard ChatGPT application. There is little research that has explored the potential of GPTs to serve as intelligent tutoring systems for learning the anatomical sciences. The objective of this study was to describe the design and explore the performance of AnatomyGPT, a customized artificial intelligence application intended for anatomical sciences education. The AnatomyGPT application was configured with GPT Builder by uploading open-source textbooks as knowledge sources and by providing pedagogical instructions for how to interact with users. The performance of AnatomyGPT was compared with ChatGPT by evaluating the responses of both applications to prompts of the National Board of Medical Examiners (NBME) sample items with respect to accuracy, rationales, and citations. AnatomyGPT achieved high scores on the NBME sample items for Gross Anatomy, Embryology, Histology, and Neuroscience and scored comparably to ChatGPT. In addition, AnatomyGPT provided several citations in the responses that it generated, while ChatGPT provided none. Both GPTs provided rationales for all sample items. The customized AnatomyGPT application demonstrated preliminary potential as an intelligent tutoring system by generating responses with increased citations as compared with the standard ChatGPT application. The findings of this study suggest that instructors and students may wish to create their own custom GPTs for teaching and learning anatomy. Future research is needed to further develop and characterize the potential of GPTs for anatomy education.

Keywords: AI (artificial intelligence); anatomy; artificial intelligence; education; embryology; histology; intelligent tutoring system; medical; medical education; undergraduate medical education.