{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T20:45:45Z","timestamp":1792097145177,"version":"4.4.0"},"reference-count":42,"publisher":"American Society of Clinical Oncology (ASCO)","issue":"4","content-domain":{"domain":["ascopubs.org"],"crossmark-restriction":true},"short-container-title":["JCO Clin Cancer Inform"],"published-print":{"date-parts":[[2026,10]]},"abstract":"\n Purpose<\/jats:title>\n Patients with cancer experience nutrition challenges, but access to registered dietitians (RDs) is limited. The purpose of this study was to determine whether a specialized Artificial Intelligence (AI) Nutrition Platform trained on curated high-quality evidence is equivalent in providing nutrition information to patients with cancer compared with oncology-credentialed RDs.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n Twenty nutrition queries were developed by an expert panel, encompassing common cancer types, symptoms, and food allergies\/preferences. These queries were administered to the AI Platform and to four nationally recruited human dietitians. Three expert reviewers with >10 years of cancer-specific nutrition experience blindly reviewed all query responses using a modified version of the Quality Assessment of Medical AI (mQAMAI) instrument, which assigns a score between 1 and 5 for accuracy, clarity, relevance, completeness, and usefulness (total quality score between 5 and 25). The primary outcome was mQAMAI total score. Equivalence was evaluated a priori using two one-sided tests (TOST). Secondary outcomes included readability and response time.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n The AI Nutrition Platform met equivalence criteria with human dietitians at \u00b13 to \u00b15 points (mean difference: 0.9 points; 90% CI, -0.27 to 2.15; TOST\n P<\/jats:italic>\n < .05), while scoring higher on individual components: clarity (4.2\n v<\/jats:italic>\n 3.9;\n P<\/jats:italic>\n = .001), relevance (4.1\n v<\/jats:italic>\n 3.9;\n P<\/jats:italic>\n = .04), and usefulness (3.8\n v<\/jats:italic>\n 3.5;\n P<\/jats:italic>\n = .02). AI responses were easier to read (Flesch-Kincaid grade level 7.2\n v<\/jats:italic>\n 9.8;\n P<\/jats:italic>\n < .001) with faster response time (8.5\n v<\/jats:italic>\n 18.5 minutes per two queries;\n P<\/jats:italic>\n < .001).\n <\/jats:p>\n <\/jats:sec>\n \n Conclusion<\/jats:title>\n The AI Platform was equivalent to human dietitians for cancer nutrition information, delivering responses with greater clarity, relevance, usefulness, and readability in less time. This tool could broaden access to nutrition support for patients in settings where access to dietitians is limited.<\/jats:p>\n <\/jats:sec>","DOI":"10.1200\/cci-25-00337","type":"journal-article","created":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T20:00:12Z","timestamp":1792094412000},"update-policy":"https:\/\/doi.org\/10.1200\/crossmark","source":"Crossref","is-referenced-by-count":0,"title":["Comparison of an Artificial Intelligence Nutrition Platform With Dietitians in Providing Nutrition Support to Patients With Cancer"],"prefix":"10.1200","volume":"10","author":[{"given":"M\u00e9lanie","family":"Guirette","sequence":"first","affiliation":[{"name":"Savor Health LLC, New York, NY"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7043-6318","authenticated-orcid":true,"given":"Marissa L.","family":"Buchan","sequence":"additional","affiliation":[{"name":"Savor Health LLC, New York, 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