This paper is in the following e-collection/theme issue:

Mobile Health (mhealth) (3426) Chatbots and Conversational Agents (722) Generative Language Models Including ChatGPT (676) Artificial Intelligence (2075) Decision Support for Health Professionals (1513) Machine Learning (2040) Innovations and Technology for Healthy Eating Education (482) Natural Language Processing (898)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/51300, first published .
An AI Dietitian for Type 2 Diabetes Mellitus Management Based on Large Language and Image Recognition Models: Preclinical Concept Validation Study

An AI Dietitian for Type 2 Diabetes Mellitus Management Based on Large Language and Image Recognition Models: Preclinical Concept Validation Study

An AI Dietitian for Type 2 Diabetes Mellitus Management Based on Large Language and Image Recognition Models: Preclinical Concept Validation Study

Authors of this article:

Haonan Sun1 Author Orcid Image ;   Kai Zhang1 Author Orcid Image ;   Wei Lan2 Author Orcid Image ;   Qiufeng Gu2 Author Orcid Image ;   Guangxiang Jiang1 Author Orcid Image ;   Xue Yang1 Author Orcid Image ;   Wanli Qin1 Author Orcid Image ;   Dongran Han1 Author Orcid Image
Article Authors Cited by (48) Tweetations (5) Metrics

Journals

  1. Sallam M, Barakat M, Sallam M. A Preliminary Checklist (METRICS) to Standardize the Design and Reporting of Studies on Generative Artificial Intelligence–Based Models in Health Care Education and Practice: Development Study Involving a Literature Review. Interactive Journal of Medical Research 2024;13:e54704 View
  2. Marchi F, Bellini E, Iandelli A, Sampieri C, Peretti G. Exploring the landscape of AI-assisted decision-making in head and neck cancer treatment: a comparative analysis of NCCN guidelines and ChatGPT responses. European Archives of Oto-Rhino-Laryngology 2024;281(4):2123 View
  3. Shiraishi M, Lee H, Kanayama K, Moriwaki Y, Okazaki M. Appropriateness of Artificial Intelligence Chatbots in Diabetic Foot Ulcer Management. The International Journal of Lower Extremity Wounds 2024 View
  4. Ma P, Tsai S, He Y, Jia X, Zhen D, Yu N, Wang Q, Ahuja J, Wei C. Large language models in food science: Innovations, applications, and future. Trends in Food Science & Technology 2024;148:104488 View
  5. Huo W, He M, Zeng Z, Bao X, Lu Y, Tian W, Feng J, Feng R. Impact Analysis of COVID-19 Pandemic on Hospital Reviews on Dianping Website in Shanghai, China: Empirical Study. Journal of Medical Internet Research 2024;26:e52992 View
  6. Sosa-Holwerda A, Park O, Albracht-Schulte K, Niraula S, Thompson L, Oldewage-Theron W. The Role of Artificial Intelligence in Nutrition Research: A Scoping Review. Nutrients 2024;16(13):2066 View
  7. Wang D, Liang J, Ye J, Li J, Li J, Zhang Q, Hu Q, Pan C, Wang D, Liu Z, Shi W, Shi D, Li F, Qu B, Zheng Y. Enhancement of the Performance of Large Language Models in Diabetes Education through Retrieval-Augmented Generation: Comparative Study. Journal of Medical Internet Research 2024;26:e58041 View
  8. Angyal V, Bertalan Á, Domján P, Dinya E. ScreenGPT – A mesterséges intelligencia alkalmazásának lehetőségei és korlátai a primer, szekunder és tercier prevencióban. Orvosi Hetilap 2024;165(16):629 View
  9. Su Y, Wang Y, He J, Wang H, A X, Jiang H, Lu W, Zhou W, Li L. Development and validation of machine-learning models of diet management for hyperphenylalaninemia: a multicenter retrospective study. BMC Medicine 2024;22(1) View
  10. Ulug E, Gunesli I, Acıkgoz Pinar A, Yildiz B. Evaluating reliability, quality, and readability of ChatGPT's nutritional recommendations for women with polycystic ovary syndrome. Nutrition Research 2025;133:46 View
  11. Ponzo V, Rosato R, Scigliano M, Onida M, Cossai S, De Vecchi M, Devecchi A, Goitre I, Favaro E, Merlo F, Sergi D, Bo S. Comparison of the Accuracy, Completeness, Reproducibility, and Consistency of Different AI Chatbots in Providing Nutritional Advice: An Exploratory Study. Journal of Clinical Medicine 2024;13(24):7810 View
  12. Allahyari M, Berjan S, El Bilali H, Ben Hassen T, Marzban S. Assessing the use of ChatGPT among agri-food researchers: A global perspective. Journal of Agriculture and Food Research 2025;19:101616 View
  13. Kassem H, Beevi A, Basheer S, Lutfi G, Cheikh Ismail L, Papandreou D. Investigation and Assessment of AI’s Role in Nutrition—An Updated Narrative Review of the Evidence. Nutrients 2025;17(1):190 View
  14. He Z, Li W. AI-Driven Management of Type 2 Diabetes in China: Opportunities and Challenges. Diabetes, Metabolic Syndrome and Obesity 2025;Volume 18:85 View
  15. Azimi I, Qi M, Wang L, Rahmani A, Li Y. Evaluation of LLMs accuracy and consistency in the registered dietitian exam through prompt engineering and knowledge retrieval. Scientific Reports 2025;15(1) View
  16. Sridhar G, Gumpeny L. Prospects and perils of ChatGPT in diabetes. World Journal of Diabetes 2025;16(3) View
  17. Mir R, Ul Haq N, Ishaq K, Safie N, Dogar A. Impact of machine learning on dietary and exercise behaviors in type 2 diabetes self-management: a systematic literature review. PeerJ Computer Science 2025;11:e2568 View
  18. O’Hara C, Kent G, Flynn A, Gibney E, Timon C. An Evaluation of ChatGPT for Nutrient Content Estimation from Meal Photographs. Nutrients 2025;17(4):607 View
  19. Guo P, Liu G, Xiang X, An R. From AI to the Table: A Systematic Review of ChatGPT’s Potential and Performance in Meal Planning and Dietary Recommendations. Dietetics 2025;4(1):7 View
  20. Xiong Y, Liu H, Zeng Y, Zhan Z, Liu W, Wang Y, Tang W, Liu C. Exploring the capabilities of GenAI for oral cancer consultations in remote consultations. BMC Oral Health 2025;25(1) View
  21. Zhang Q, Chen Y, Liang X. Intelligent visual analytics for food safety: A comprehensive review. Computer Science Review 2025;57:100739 View
  22. Nimri R, Phillip M, Clements M, Kovatchev B. Closed-Loop, Artificial Intelligence-Based Decision Support Systems, and Data Science. Diabetes Technology & Therapeutics 2025;27(S1):S64 View
  23. You Q, Li X, Shi L, Rao Z, Hu W. Still a Long Way to Go, the Potential of ChatGPT in Personalized Dietary Prescription, From a Perspective of a Clinical Dietitian. Journal of Renal Nutrition 2025;35(4):510 View
  24. Bergling K, Wang L, Shivakumar O, Nandorine Ban A, Moore L, Ginsberg N, Kooman J, Duncan N, Kotanko P, Zhang H. From bytes to bites: application of large language models to enhance nutritional recommendations. Clinical Kidney Journal 2025;18(4) View
  25. Maslinski J, Grasfield R, Awasthi R, Mishra S, Mahapatra D, Mathur P. Understanding Large Language Models in Healthcare: A Guide to Clinical Implementation and Interpreting Publications. Cureus 2025 View
  26. Mo Y, Zhao F, Yuan L, Xing Q, Zhou Y, Wu Q, Li C, Lin J, Wu H, Deng S, Zhang M. Healthcare providers’ perceptions of artificial intelligence in diabetes care: A cross-sectional study in China. International Journal of Nursing Sciences 2025;12(3):218 View
  27. Saad A, Islam M. Navigating nutrients: A scoping review on real-time food nutrition classification and recommendation systems. Computers in Biology and Medicine 2025;192:110306 View
  28. Boie S, Glastetter E, Lux M, Balzer F, von Kalle C, Lenz C, Müller U. Evaluating a Chatbot as a Companion for Patients With Breast Cancer: Collaborative Pilot Study. JMIR Cancer 2025;11:e68426 View
  29. Angyal V, Bertalan Á, Domján P, Dinya E. Exploring the possibilities and limitations of customized large language model to support and improve cervical cancer screening. BMC Medical Informatics and Decision Making 2025;25(1) View
  30. Zhang L, Yang G, Yuan J, Yuan S, Zhang J, Chen J, Tang M, Zhang Y, Lin J, Zhao L, Yin Y. Enhancing pediatric asthma management in underdeveloped regions through ChatGPT training for doctors: a randomized controlled trial. Frontiers in Pediatrics 2025;13 View
  31. Wang S, An M, Lin S, Kuy S, Li D. Artificial intelligence and digital twins: revolutionizing diabetes care for tomorrow. Intelligent Medicine 2025;5(3):173 View
  32. Belkhouribchia J, Pen J. Large language models in clinical nutrition: an overview of its applications, capabilities, limitations, and potential future prospects. Frontiers in Nutrition 2025;12 View
  33. Bhuiyan M, Saha B, Satter M. Harnessing Artificial Intelligence and Precision Diets for Brain Health and Cognitive Resilience. The Journal of Nutrition 2025;155(10):3179 View
  34. Yang E, Garcia T, Williams H, Kumar B, Ramé M, Rivera E, Ma Y, Amar J, Catalani C, Jia Y. A Behavioral Science-Informed Agentic Workflow for Personalized Nutrition Coaching: Development and Validation Study. JMIR Formative Research 2025;9:e75421 View
  35. Alqahtani N. Artificial Intelligence in Dietary Recommendations for Type 1 Diabetes: Evaluating the Performance of ChatGPT-4o, Bing AI, and Bard AI. F1000Research 2025;14:812 View
  36. Arslan S. Artificial intelligence in food safety and nutrition practices: opportunities and risks. Academia Nutrition and Dietetics 2025;2(3) View
  37. Li C, Li W, Shao Y, Xu Z, Song J, Wang Y. A Scoping Review of Artificial Intelligence-Based Health Education Interventions for Patients with Type 2 Diabetes. Diabetes, Metabolic Syndrome and Obesity 2025;Volume 18:3539 View
  38. Bayram H, Ozturkcan A. Applications of generative and predictive AI in nutrition and dietetics: a narrative review. Informatics for Health and Social Care 2025:1 View
  39. Hieronimus B, Lopez-Aguirre M, Birringer M, Podszun M. GenAI in nutritional sciences (GAINS): A systematic review and reporting framework for future research. Nutrition Research 2025;143:66 View
  40. Hsuan C, Lee Y, Hsu H, Ouyang C, Yeh W, Tang W. Comparison of Accuracy in the Evaluation of Nutritional Labels on Commercial Ready-to-Eat Meal Boxes Between Professional Nutritionists and Chatbots. Nutrients 2025;17(19):3044 View
  41. García-Rudolph A, Hernandez-Pena E, del Cacho N, Teixidó-Font C, Wright M, Opisso E. GPT-4o in Nutrition for Inpatients Undergoing Post-Stroke Rehabilitation: Identifying Dietary Errors, Exploring Expert-AI Rationale Differences, and Structuring AI-Expert Collaboration. Journal of the American Nutrition Association 2025:1 View

Books/Policy Documents

  1. Gong F, Sha H, Liu R, Wu T, Liu B, Wang H. Health Information Processing. View
  2. Chan K, Liu S. Lifestyle Medicine. View
  3. Flores Ñahuis S, Paredes Villagra R, Canaval Sánchez L. Information Management and Big Data. View
  4. Hendi N, Abouelmagd M, Sharkawy A, Jasim E, Amin A. Feeding the Mind: The Connection Between Diet, Drugs, and Mental Health Volume 2. View

Conference Proceedings

  1. Tsiantis V, Konstantinidis D, Dimitropoulos K. Proceedings of the 17th International Conference on PErvasive Technologies Related to Assistive Environments. ChatGPT in Nutrition: Trends Challenges and Future Directions View
  2. Abbasian M, Yang Z, Khatibi E, Zhang P, Nagesh N, Azimi I, Jain R, Rahmani A. 2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). Knowledge-Infused LLM-Powered Conversational Health Agent: A Case Study for Diabetes Patients View
  3. Kanjalkar J, Kanjalkar P, Khanke R, Mane R, Kharat K, Kolhe K. 2024 International Conference on Integrated Intelligence and Communication Systems (ICIICS). An AI-Driven Framework for Personalized Diet Generation and Nutrition Suggestions Using Machine Learning, Computer Vision and NLP View