{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T16:12:33Z","timestamp":1791994353937,"version":"4.4.0"},"reference-count":22,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Form Res"],"abstract":"\n Background<\/jats:title>\n Assessment of medical information provided by artificial intelligence (AI) chatbots like ChatGPT and Google\u2019s Gemini and comparison with international guidelines is a burgeoning area of research. These AI models are increasingly being considered for their potential to support clinical decision-making and patient education. However, their accuracy and reliability in delivering medical information that aligns with established guidelines remain under scrutiny.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n This study aims to assess the accuracy of medical information generated by ChatGPT and Gemini and its alignment with international guidelines for sepsis management.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n ChatGPT and Gemini were asked 18 questions about the Surviving Sepsis Campaign guidelines, and the responses were evaluated by 7 independent intensive care physicians. The responses generated were scored as follows: 3=correct, complete, and accurate; 2=correct but incomplete or inaccurate; and 1=incorrect. This scoring system was chosen to provide a clear and straightforward assessment of the accuracy and completeness of the responses. The Fleiss \u03ba test was used to assess the agreement between evaluators, and the Mann-Whitney U test was used to test for the significance of differences between the correct responses generated by ChatGPT and Gemini.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n ChatGPT provided 5 (28%) perfect responses, 12 (67%) nearly perfect responses, and 1 (5%) low-quality response, with substantial agreement among the evaluators (Fleiss \u03ba=0.656). Gemini, on the other hand, provided 3 (17%) perfect responses, 14 (78%) nearly perfect responses, and 1 (5%) low-quality response, with moderate agreement among the evaluators (Fleiss \u03ba=0.582). The Mann-Whitney U test revealed no statistically significant difference between the two platforms (P=.48).<\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n ChatGPT and Gemini both demonstrated potential for generating medical information. Despite their current limitations, both showed promise as complementary tools in patient education and clinical decision-making. The medical information generated by ChatGPT and Gemini still needs ongoing evaluation regarding its accuracy and alignment with international guidelines in different medical domains, particularly in the sepsis field.<\/jats:p>\n <\/jats:sec>","DOI":"10.2196\/84251","type":"journal-article","created":{"date-parts":[[2025,12,17]],"date-time":"2025-12-17T21:45:07Z","timestamp":1766007907000},"page":"e84251","source":"Crossref","is-referenced-by-count":5,"title":["Evaluating the Accuracy of Medical Information Generated by ChatGPT and Gemini and Its Alignment With International Clinical Guidelines From the Surviving Sepsis Campaign: Comparative Study"],"prefix":"10.2196","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2371-2145","authenticated-orcid":false,"given":"Dina","family":"Kutbi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9537-3245","authenticated-orcid":false,"given":"Ehab","family":"Abou-Bakr","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6204-4795","authenticated-orcid":false,"given":"Hassan Mousa","family":"Haidar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1010","published-online":{"date-parts":[[2025,12,17]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.2196\/48808"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.18683\/germs.2024.1419"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1515\/mr-2023-0039"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1097\/MD.0000000000037458"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.7759\/cureus.60675"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.22599\/bioj.377"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1136\/jitc-2023-008599"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.iotcps.2023.04.003"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1186\/s40561-024-00310-z"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1099\/acmi.0.000790.v3"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.3928\/01484834-20240426-01"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1097\/CCM.0000000000005337"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/s10916-023-01925-4"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pdig.0000198"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1001\/jamaoncol.2023.2947"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1001\/jamaoncol.2023.2954"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.7759\/cureus.45890"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1038\/s41433-024-02958-w"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.52225\/narra.v3i1.103"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1186\/s13018-024-04996-2"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1186\/s12911-024-02619-8"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.21037\/jmai-23-70"}],"container-title":["JMIR Formative Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/formative.jmir.org\/2025\/1\/e84251","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T18:18:24Z","timestamp":1782843504000},"score":1,"resource":{"primary":{"URL":"https:\/\/formative.jmir.org\/2025\/1\/e84251"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,17]]},"references-count":22,"URL":"https:\/\/doi.org\/10.2196\/84251","relation":{"has-preprint":[{"id-type":"doi","id":"10.2196\/preprints.84251","asserted-by":"object"}]},"ISSN":["2561-326X"],"issn-type":[{"value":"2561-326X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,17]]}}}