# Analyzing the Performance of ChatGPT in Cardiology and Vascular Pathologies

arXiv: https://arxiv.org/abs/2307.02518 · HTML: https://mlsanity.com/paper/2307.02518/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 6 references that are in the map.
- First posted on arXiv 15 Apr 2023.

## Builds on (most cited first, 1 of 1)

- [Unlocking the Potential of ChatGPT: A Comprehensive Exploration of its Applications, Advantages, Limitations, and Future Directions in Natural Language Processing](https://mlsanity.com/paper/2304.02017/) (2023)

## Built on by (most cited first, 1 of 1)

- [Sentiment Analysis of Citations in Scientific Articles Using ChatGPT: Identifying Potential Biases and Conflicts of Interest](https://mlsanity.com/paper/2404.01800/) (2024)

## Abstract (arXiv)

The article aims to analyze the performance of ChatGPT, a large language model developed by OpenAI, in the context of cardiology and vascular pathologies. The study evaluated the accuracy of ChatGPT in answering challenging multiple-choice questions (QCM) using a dataset of 190 questions from the Siamois-QCM platform. The goal was to assess ChatGPT potential as a valuable tool in medical education compared to two well-ranked students of medicine. The results showed that ChatGPT outperformed the students, scoring 175 out of 190 correct answers with a percentage of 92.10%, while the two students achieved scores of 163 and 159 with percentages of 85.78% and 82.63%, respectively. These results showcase how ChatGPT has the potential to be highly effective in the fields of cardiology and vascular pathologies by providing accurate answers to relevant questions.