# Evaluating ChatGPT 4.0 as a Tool for Nuclear Medicine Board Preparation

## TL;DR

This study evaluates how well ChatGPT 4.0 can help nuclear medicine students prepare for certification exams by answering practice questions.

## Contribution

The study is one of the first to assess ChatGPT 4.0's accuracy on nuclear medicine board questions, revealing topic-specific performance variations.

## Key findings

- ChatGPT 4.0 achieved an overall accuracy of 86.95% on nuclear medicine board questions.
- The model performed poorly in pediatric nuclear medicine (75%) but perfectly in nuclear cardiology and radiopharmacy.
- Performance did not correlate with the number of questions per chapter.

## Abstract

Due to their potential use in medical education, large language models (LLMs), a type of generative artificial intelligence (AI), have become increasingly popular. The accuracy of ChatGPT 4.0 (OpenAI, San Francisco, CA) in responding to multiple-choice questions from a standardized board preparation resource for nuclear medicine certification examinations is assessed in this study. A total of 115 text-based questions from 12 chapters were chosen in total; image-dependent questions were not included because of ChatGPT's restrictions on text-only input. Section-by-section and overall accuracy were calculated by comparing the model's replies to the official answer key. ChatGPT performed the worst in pediatric nuclear medicine (75%), while achieving a total accuracy of 86.95%. It received perfect marks in nuclear cardiology and radiopharmacy. Interestingly, model performance did not correlate with the quantity of questions per chapter. According to these results, ChatGPT might be a useful addition to radiology education; nonetheless, topic-level performance variations and opaque reasoning underscore the need for more research prior to wider educational integration.