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This study compares concordance, functional characteristics, accessibility, and innovation of ChatGPT-generated nutritional recommendations with CSCO, CNS, and ESPEN guidance across six nutrition issues. Expert evaluation, readability metrics, semantic similarity, and patient-centered assessments show partial guideline alignment and superior patient-centered clarity and self-management support for ChatGPT, while guidelines score higher on clinical feasibility, evidence, and population applicability.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":35,"@type":76,"position":81},"https://docshare.wps.com/document/healthcare/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/feeding-intelligence-comparative-evaluation-of-chatgpt-and-clinical-guidelines-for-nutritional-management-in-head-and-neck-cancer/406969/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/feeding-intelligence-comparative-evaluation-of-chatgpt-and-clinical-guidelines-for-nutritional-management-in-head-and-neck-cancer/406969.png","ImageObject",300,407,{"name":92,"@type":93},"PakDamar76","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-11-01","2026-09-28",true,{"@type":102,"interactionType":103,"userInteractionCount":34},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What does the study compare between ChatGPT and clinical guidelines?","Question",{"text":112,"@type":113},"It evaluates concordance, functional characteristics, patient accessibility, and innovation of ChatGPT-generated nutritional recommendations against guidelines from CSCO, CNS, and ESPEN.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"Which nutrition-related issues are analyzed?",{"text":117,"@type":113},"The analysis covers anorexia/cachexia, dysphagia, oral mucositis, unintentional weight loss, gastrointestinal intolerance, and nutritional monitoring.",{"name":119,"@type":110,"acceptedAnswer":120},"How do the results differ for clinical feasibility and evidence support?",{"text":121,"@type":113},"Guidelines score higher for clinical feasibility, evidence-based support, and population applicability, with statistically significant between-group differences for those domains.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},406969,1791322234,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":34,"category_name":35,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":34,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":145,"preview_page_count":4},962090893057,"https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d","Shen et al. Journal of Translational Medicine (2025) 23:1437  \n[https://doi.org/10.1186/s12967-025-07477-0](https://doi.org/10.1186/s12967-025-07477-0)  \nJournal of Translational Medicine  \nRESEARCH Open Access  \nFeeding intelligence: comparative evaluation of ChatGPT and clinical guidelines for nutritional management in head and neck cancer  \nShasha Shen 1, Kai Zhou2, Mingna Wu 1, Dahai Liu3, Xiaotong Shen4, Peijie Li5, Ying Xu 1, Sijia Zheng 1 and  \nXiaoxia Gou 1*  \nAbstract  \nBackground Artificial intelligence (AI) tools such as ChatGPT are increasingly applied in digital health and patient education, yet their alignment with established clinical guidelines for cancer-related nutritional management remains unclear.  \nObjective This study aimed to evaluate the concordance, functional characteristics, patient accessibility, and innovation of ChatGPT-generated nutritional recommendations compared with clinical guidelines from the Chinese Society of Clinical Oncology (CSCO), Chinese Nutrition Society (CNS), and European Society for Clinical Nutrition and Metabolism (ESPEN) .  \nMethods We analyzed ChatGPT responses across six key nutrition-related issues—anorexia/cachexia, dysphagia, oral mucositis, unintentional weight loss, gastrointestinal intolerance, and nutritional monitoring—and compared them with guideline recommendations. Expert evaluation (n = 5), readability metrics, semantic similarity (TF-IDF), and patient-centered assessments were conducted to compare personalization, innovation, clinical feasibility, evidencebased support, population applicability, clarity, and self-management guidance.  \nResults ChatGPT recommendations aligned with at least one guideline in 50.0–64. 3% of cases, highest fordysphagia (64 . 3%), and included general strategies such as small frequent meals, texture modification, hydration, and high-protein/high-calorie intake. ChatGPT-specific suggestions (8 .3–18. 2%) focused on lifestyle and behavioral interventions, including mindful eating, music therapy, and wearable diet trackers. Expert ratings indicated higher personalization (4 . 3/5) and innovation (4 . 6/5) for ChatGPT, whereas guidelines scored higher for clinical feasibility (4 . 7/5), evidence-based support (4 . 9/5), and population applicability (4 . 8/5) . Between-group differences were statistically significant for clinical feasibility, evidence-based support, and applicability (all p \u003C 0. 01; 95% CI for mean differences: 0 .62–1. 12), whereas personalization showed no significant difference (p = 0 . 063) . ChatGPT exhibited superior patient-centered performance in clarity (4 . 5 vs. 3. 2, p = 0 . 004, 95% CI: 0 .47–2. 13) and self-management  \n*Correspondence: Xiaoxia Gou [gouxx2020@163.com](gouxx2020@163.com)  \nFull list of author information is available at the end of the article  \n© The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit [http://creati](http://creati)[vecommons.org/l](vecommons.org/l)icenses/by-nc-nd/4.0/.  \nShen et al. Journal of Translational Medicine (2025) 23:1437 Page 2 of 15  \nguidance (4","cbCaiojVT53OKyNd","https://ap.wps.com/l/cbCaiojVT53OKyNd","pdf",3939594,15,"English","# Abstract\n# Introduction\n## Malnutrition in head and neck cancer\n## Clinical nutrition guidelines and risk assessment","[{\"question\":\"What does the study compare between ChatGPT and clinical guidelines?\",\"answer\":\"It evaluates concordance, functional characteristics, patient accessibility, and innovation of ChatGPT-generated nutritional recommendations against guidelines from CSCO, CNS, and ESPEN.\"},{\"question\":\"Which nutrition-related issues are analyzed?\",\"answer\":\"The analysis covers anorexia/cachexia, dysphagia, oral mucositis, unintentional weight loss, gastrointestinal intolerance, and nutritional monitoring.\"},{\"question\":\"How do the results differ for clinical feasibility and evidence support?\",\"answer\":\"Guidelines score higher for clinical feasibility, evidence-based support, and population applicability, with statistically significant between-group differences for those domains.\"}]","Feeding intelligence - comparative evaluation of ChatGPT and clinical guidelines for nutritional management in head and neck cancer | PDF",1790569219,38]