{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T16:21:00Z","timestamp":1791908460819,"version":"4.3.4"},"reference-count":29,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2025,11,6]],"date-time":"2025-11-06T00:00:00Z","timestamp":1762387200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2025,11,6]],"date-time":"2025-11-06T00:00:00Z","timestamp":1762387200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/100006108","name":"National Center for Advancing Translational Sciences","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006108","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["aspenjournals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Nut in Clin Prac"],"published-print":{"date-parts":[[2026,4]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Clinical nutrition (CN) is becoming increasingly complex because of the rising prevalence of chronic illness, cancer, and malnutrition\u2010related conditions such as short bowel syndrome and refeeding syndrome. Despite its clinical significance, nutrition education among US physicians remains limited. Simultaneously, large language model (LLM)\u2013based artificial intelligence assistants (AIAs) have emerged as tools to support complex clinical decision\u2010making but remain largely untested in CN.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This retrospective study evaluated four LLM\u2010based AIAs\u2014ChatGPT (OpenAI), OpenEvidence (OpenEvidence Inc), Gemini (Google, Google DeepMind), and Copilot (Microsoft Corporation)\u2014using five complex CN cases from our nutrition support service. Each AIA was queried with patient\u2010specific CN questions. Responses were blinded and reviewed by five physician CN experts using an eight\u2010item assessment tool evaluating clarity, relevance, evidence, and clinical utility.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>All AIAs produced clinically appropriate responses, with Gemini scoring highest in relevance (4.04) and clarity (4.16). Overall satisfaction scores ranged from 3.08 (Copilot) to 3.84 (Gemini). Citation quality and originality of insights varied and were generally limited, and no consistent differences in performance were observed across the five cases among the four AIAs.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>LLM\u2010based AIAs can reliably replicate expert reasoning in CN. Although not yet a source of novel clinical insights, the true potential of this approach may lie in its application among physicians without specialized expertise in CN, helping to bridge existing knowledge gaps in nutrition care. Presenting full clinical cases, as shown in this study, could support AIA\u2010enabled e\u2010consultation in the future, thereby addressing gaps in CN education.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/ncp.70062","type":"journal-article","created":{"date-parts":[[2025,11,7]],"date-time":"2025-11-07T05:00:06Z","timestamp":1762491606000},"page":"581-588","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Artificial intelligence (AI) in nutrition: A case\u2010based comparison of generative AI models"],"prefix":"10.1002","volume":"41","author":[{"given":"Ryan T.","family":"Hurt","sequence":"first","affiliation":[{"name":"Division of General Internal Medicine Mayo Clinic Rochester Minnesota USA"},{"name":"Division of Endocrinology Mayo Clinic Rochester Minnesota 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