Systematic Reviews
Copyright ©The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Cardiol. Aug 26, 2025; 17(8): 110489
Published online Aug 26, 2025. doi: 10.4330/wjc.v17.i8.110489
Comparison of ChatGPT and DeepSeek large language models in the diagnosis of pericarditis
Aman Goyal, Samia Aziz Sulaiman, Abdallah Alaarag, Waseem Hoshan, Priya Goyal, Viraj Shah, Mohamed Daoud, Gauranga Mahalwar, Abu Baker Sheikh
Aman Goyal, Gauranga Mahalwar, Department of Internal Medicine, Cleveland Clinic Foundation, Cleveland, OH 44195, United States
Samia Aziz Sulaiman, Abdallah Alaarag, Waseem Hoshan, School of Medicine, The University of Jordan, Amman 11942, Jordan
Priya Goyal, Department of Internal Medicine, Dayanand Medical College and Hospital, Ludhiana 141001, Punjab, India
Viraj Shah, Department of Cardiology, Wellstar MCG Health, Augusta, GA 30912, United States
Mohamed Daoud, Department of Internal Medicine, Bogomolets National Medical University, Kyiv 01601, Ukraine
Abu Baker Sheikh, Department of Internal Medicine, University of New Mexico, Albuquerque, NM 87131, United States
Co-first authors: Aman Goyal and Samia Aziz Sulaiman.
Author contributions: Goyal A, Sulaiman SA, Alaarag A, and Hoshan W conceptualization, data curation, formal analysis, visualization, writing-original draft, writing-review & editing; Goyal P, Shah V, Daoud M, Mahalwar G, and Sheikh AB conceptualization, resources, formal analysis, writing-original draft, writing-review & editing. Goyal A and Sulaiman SA contributed equally to this work as co-first authors.
Conflict-of-interest statement: The authors declare no conflicts of interest.
PRISMA 2009 Checklist statement: The authors have read the PRISMA 2009 Checklist, and the manuscript was prepared and revised according to the PRISMA 2009 Checklist.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Mohamed Daoud, MD, Department of Internal Medicine, Bogomolets National Medical University, No. 13 Tarasa Shevchenko Blvd, Kyiv 01601, Ukraine. drmohameddaoudmd@gmail.com
Received: June 9, 2025
Revised: June 13, 2025
Accepted: July 31, 2025
Published online: August 26, 2025
Processing time: 74 Days and 22.5 Hours
Core Tip

Core Tip: This study evaluates the capabilities of large language models (LLMs), ChatGPT o1 and DeepSeek-R1, in the risk stratification of acute pericarditis, where delayed diagnosis may lead to significant complications. While both LLMs show similar performance and promise as supportive tools in identifying high-risk presentations, their current limitations in recognizing atypical symptom profiles underscore the need for further refinement. Future research should focus on improving model sensitivity to demographic and clinical variability to ensure broader applicability and safety in real-world settings.