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

Mobile Health (mhealth) (2941) Chatbots and Conversational Agents (531) Generative Language Models Including ChatGPT (311) Artificial Intelligence (1371) Decision Support for Health Professionals (1185) Machine Learning (1465) Innovations and Technology for Healthy Eating Education (414) Natural Language Processing (692)

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 (10) Tweetations (5) Metrics

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  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