Analyzing the Performance of ChatGPT in Cardiology and Vascular Pathologies

preprint OA: closed CC-BY-4.0
📄 Open PDF View at publisher

Abstract

Abstract 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 ChatGPT's accuracy in answering challenging multiple-choice questions (QCM) using a dataset of 190 questions from the Siamois-QCM platform. The goal was to assess ChatGPT's 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.

My notes (saved in your browser only)

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. The paper's references may be in our DB but unresolved to ``paper_id`` (resolution happens at ingest when the cited DOI matches a row we already have). Run the cross-source citation reconcile pass to retry.

Source provenance

europepmc
last seen: 2026-05-19T01:45:01.086888+00:00
unpaywall
last seen: 2026-06-02T02:00:03.124865+00:00
License: CC-BY-4.0