{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T22:19:46Z","timestamp":1784326786021,"version":"3.55.0"},"reference-count":33,"publisher":"SAGE Publications","issue":"4","license":[{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"name":"Foundation of Zhejiang Provincial Education Department","award":["Y202249328"],"award-info":[{"award-number":["Y202249328"]}]},{"name":"Foundation of Zhejiang Provincial Education Department","award":["Y202558666"],"award-info":[{"award-number":["Y202558666"]}]},{"name":"Foundation of The Fourth Affiliated Hospital Zhejiang University School of Medicine","award":["JG20230203"],"award-info":[{"award-number":["JG20230203"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["J Int Med Res"],"published-print":{"date-parts":[[2026,4]]},"abstract":"<jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To evaluate the accuracy of ChatGPT and DeepSeek in answering guideline-based clinical questions in cardiology.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>In August 2025, responses generated from four large language models to eight clinical questions based on the 2025 Society for Cardiovascular Angiography &amp; Interventions\/Heart Rhythm Society guidelines were evaluated. Three cardiologists independently rated accuracy using a six-point Likert scale: (a) completely incorrect; (b) more incorrect than correct; (c) nearly equally correct and incorrect; (d) more correct than incorrect; (e) nearly all correct; and (f) completely correct. Reproducibility (Fleiss\u2019 kappa coefficient, five repeated queries) and inter-rater reliability (intraclass correlation coefficient) were assessed.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The median (interquartile range) accuracy scores were 5.5 (5, 6) for ChatGPT-5, 6 (5, 6) for ChatGPT-4o, and 5 (4, 6) for both DeepSeek-R1 and DeepSeek-V3, with a significant overall difference (p\u2009&lt;\u20090.001). Pairwise comparisons showed significantly higher accuracy for ChatGPT models than for DeepSeek models (all p\u2009&lt;\u20090.001), whereas no significant differences were observed between ChatGPT-5 and ChatGPT-4o (p\u2009=\u20090.518) or between DeepSeek-R1 and DeepSeek-V3 (p\u2009=\u20090.812). Reproducibility (Fleiss\u2019 kappa coefficient) was excellent for ChatGPT-5 (0.803) and good for ChatGPT-4o (0.574), DeepSeek-R1 (0.577), and DeepSeek-V3 (0.618). Overall inter-rater reliability was moderate (intraclass correlation coefficient\u2009=\u20090.463).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>ChatGPT and DeepSeek demonstrated high accuracy and reproducibility but moderate inter-rater reliability, necessitating further validation for educational use.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/03000605261438348","type":"journal-article","created":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T03:59:50Z","timestamp":1776139190000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":1,"title":["Accuracy of ChatGPT and DeepSeek in answering clinical questions from the 2025 Society for Cardiovascular Angiography &amp; Interventions\/Heart Rhythm Society left atrial appendage occlusion guidelines"],"prefix":"10.1177","volume":"54","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4242-7072","authenticated-orcid":false,"given":"Yunpeng","family":"Jin","sequence":"first","affiliation":[{"name":"Department of Cardiology, The Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9725-6923","authenticated-orcid":false,"given":"Chao","family":"Feng","sequence":"additional","affiliation":[{"name":"Department of Cardiology, The Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianqiang","family":"Zhao","sequence":"additional","affiliation":[{"name":"Department of Cardiology, The Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenting","family":"Lin","sequence":"additional","affiliation":[{"name":"Department of Cardiology, The Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bin","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Nursing, The Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,4,13]]},"reference":[{"key":"e_1_3_10_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cjco.2025.03.013"},{"key":"e_1_3_10_3_2","doi-asserted-by":"publisher","DOI":"10.1001\/jamanetworkopen.2025.12994"},{"key":"e_1_3_10_4_2","doi-asserted-by":"publisher","DOI":"10.2459\/JCM.0000000000001664"},{"key":"e_1_3_10_5_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pdig.0000198"},{"key":"e_1_3_10_6_2","doi-asserted-by":"publisher","DOI":"10.1093\/ehjdh\/ztad029"},{"key":"e_1_3_10_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.nepr.2022.103537"},{"key":"e_1_3_10_8_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0290691"},{"key":"e_1_3_10_9_2","first-page":"e49604","article-title":"Artificial intelligence revolutionizing the field of medical education","volume":"15","author":"Narayanan S","year":"2023","unstructured":"Narayanan S, Ramakrishnan R, Durairaj E, et\u00a0al. 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