{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,18]],"date-time":"2026-05-18T12:15:21Z","timestamp":1779106521297,"version":"3.51.4"},"reference-count":25,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T00:00:00Z","timestamp":1776729600000},"content-version":"vor","delay-in-days":20,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Evaluation Clinical Practice"],"published-print":{"date-parts":[[2026,4]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Crohn's disease (CD) requires accurate, guideline\u2010based diagnosis and management, yet the growing complexity of therapeutic options and international recommendations creates challenges for timely clinical decision\u2010making. Large language models (LLMs) have emerged as potential tools for clinical decision support, but their performance in guideline\u2010based gastroenterology remains insufficiently characterized.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We conducted a structured comparative evaluation of ChatGPT 5.0 and DeepSeek R1 using 47 standardized clinical questions derived from the 2023 Chinese guidelines for the diagnosis and treatment of CD. Each question was submitted independently to both models under identical conditions, without iterative clarification. Responses were assessed across multiple dimensions, including coverage, guideline consistency, agreement, response length, detail coverage, readability, and structural clarity. Domain\u2010specific analyses were performed for diagnostic, therapeutic, and surgical\/management questions.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Both models demonstrated high alignment with guideline\u2010based recommendations, with guideline consistency rates of 93% for ChatGPT 5.0% and 96% for DeepSeek R1, and an inter\u2010model agreement rate of approximately 87%. ChatGPT 5.0 showed complete detail coverage across diagnostic, therapeutic, and surgical\/management domains (100%) and generated shorter, more concise responses (mean 208 words; range 142\u2013300) with higher readability (mean 4.6\/5). DeepSeek R1 achieved 87.5% overall detail coverage, with slightly lower performance in diagnostic (88.2%) and therapeutic (85.2%) categories but equivalent performance in surgical\/management questions. Its responses were longer (mean 291 words; range 128\u2013417) and incorporated more trial data, drug comparisons, and cross\u2010guideline references, although readability was lower (mean 3.4\/5).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>ChatGPT 5.0 and DeepSeek R1 demonstrated distinct yet complementary strengths in guideline\u2010based CD applications. ChatGPT 5.0 functioned more effectively as a clinical\u2010ready assistant by providing concise, highly readable, and actionable outputs, whereas DeepSeek R1 was better suited to academic and research\u2010oriented contexts through deeper evidence integration. A hybrid workflow combining rapid point\u2010of\u2010care support from ChatGPT 5.0 with evidence synthesis from DeepSeek R1 may offer optimal utility. Further real\u2010world validation is needed before routine clinical implementation.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/jep.70440","type":"journal-article","created":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T18:18:01Z","timestamp":1776795481000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Detail Coverage and Evidence Integration: Evaluating ChatGPT 5.0 and DeepSeek R1 in Guideline\u2010Based Crohn's Disease Applications"],"prefix":"10.1111","volume":"32","author":[{"given":"Hutao","family":"Zhou","sequence":"first","affiliation":[{"name":"Yixing People's Hospital Yixing, Wuxi Jiangsu Province China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tao","family":"Yuan","sequence":"additional","affiliation":[{"name":"Yixing People's Hospital Yixing, Wuxi Jiangsu Province China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yueji","family":"Ning","sequence":"additional","affiliation":[{"name":"Yixing People's Hospital Yixing, Wuxi Jiangsu Province China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Boneng","family":"Mao","sequence":"additional","affiliation":[{"name":"Yixing People's Hospital Yixing, Wuxi Jiangsu Province China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-4715-3278","authenticated-orcid":false,"given":"Mengping","family":"Zhu","sequence":"additional","affiliation":[{"name":"Yixing People's Hospital Yixing, Wuxi Jiangsu Province China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2026,4,21]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(23)02586-2"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cgh.2020.01.028"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1053\/j.gastro.2011.10.001"},{"key":"e_1_2_9_5_1","first-page":"2763","article-title":"Worldwide Incidence and Prevalence of Inflammatory Bowel Disease in the 21st Century: Systematic Review","volume":"389","author":"Ng S. C.","year":"2018","journal-title":"Lancet"},{"issue":"2","key":"e_1_2_9_6_1","first-page":"100","article-title":"Chinese Guidelines for the Diagnosis and Treatment of Crohn's Disease (2023, Guangzhou)","volume":"44","author":"Chinese Society of Gastroenterology, Inflammatory Bowel Disease Group","year":"2024","journal-title":"Chinese Journal of Digestive Diseases"},{"key":"e_1_2_9_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(16)31711-1"},{"key":"e_1_2_9_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/S2468-1253(19)30333-4"},{"key":"e_1_2_9_9_1","doi-asserted-by":"publisher","DOI":"10.1038\/ajg.2015.233"},{"key":"e_1_2_9_10_1","doi-asserted-by":"publisher","DOI":"10.1053\/j.gastro.2020.12.031"},{"key":"e_1_2_9_11_1","doi-asserted-by":"publisher","DOI":"10.3748\/wjg.v30.i1.50"},{"key":"e_1_2_9_12_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41575-024-00935-y"},{"key":"e_1_2_9_13_1","doi-asserted-by":"publisher","DOI":"10.1001\/jamanetworkopen.2023.36483"},{"key":"e_1_2_9_14_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-018-0300-7"},{"key":"e_1_2_9_15_1","doi-asserted-by":"publisher","DOI":"10.1136\/svn-2017-000101"},{"key":"e_1_2_9_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.imed.2025.03.001"},{"key":"e_1_2_9_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(02)08512-4"},{"key":"e_1_2_9_18_1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa067594"},{"key":"e_1_2_9_19_1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa1215734"},{"key":"e_1_2_9_20_1","unstructured":"OpenAI. ChatGPT 5.0: Large Language Model for General\u2010purpose Reasoning And Clinical Decision Support. Technical Report. OpenAI. 2025."},{"key":"e_1_2_9_21_1","unstructured":"DeepSeek AI Lab. DeepSeek R1: Efficient Large Language Model Optimized for Detailed Academic Applications. White Paper. DeepSeek. 2025."},{"key":"e_1_2_9_22_1","doi-asserted-by":"publisher","DOI":"10.1093\/ecco-jcc\/jjac187"},{"key":"e_1_2_9_23_1","doi-asserted-by":"publisher","DOI":"10.1001\/jamainternmed.2018.7117"},{"key":"e_1_2_9_24_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-021-01614-0"},{"key":"e_1_2_9_25_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-020-1034-x"},{"key":"e_1_2_9_26_1","article-title":"AI in Medicine: The Challenges of Large Language Models","author":"Heaven W. D.","year":"2023","journal-title":"MIT Technology Review"}],"container-title":["Journal of Evaluation in Clinical Practice"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1111\/jep.70440","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1111\/jep.70440","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1111\/jep.70440","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,18]],"date-time":"2026-05-18T11:34:33Z","timestamp":1779104073000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1111\/jep.70440"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4]]},"references-count":25,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2026,4]]}},"alternative-id":["10.1111\/jep.70440"],"URL":"https:\/\/doi.org\/10.1111\/jep.70440","archive":["Portico"],"relation":{},"ISSN":["1356-1294","1365-2753"],"issn-type":[{"value":"1356-1294","type":"print"},{"value":"1365-2753","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,4]]},"assertion":[{"value":"2025-09-09","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-04-07","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-04-21","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e70440"}}