Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Comparative Study
. 2025 Jan 7;17(2):206.
doi: 10.3390/nu17020206.

Diet Quality and Caloric Accuracy in AI-Generated Diet Plans: A Comparative Study Across Chatbots

Hüsna Kaya Kaçar  1 , Ömer Furkan Kaçar  2   3   4 , Amanda Avery  5
Affiliations
Comparative Study

Diet Quality and Caloric Accuracy in AI-Generated Diet Plans: A Comparative Study Across Chatbots

Hüsna Kaya Kaçar et al. Nutrients. .

Abstract

Background/Objectives: With the rise of artificial intelligence (AI) in nutrition and healthcare, AI-driven chatbots are increasingly recognised as potential tools for generating personalised diet plans. This study aimed to evaluate the capabilities of three popular chatbots-Gemini, Microsoft Copilot, and ChatGPT 4.0-in designing weight-loss diet plans across varying caloric levels and genders. Methods: This comparative study assessed the diet quality of meal plans generated by the chatbots across a calorie range of 1400-1800 kcal, using identical prompts tailored to male and female profiles. The Diet Quality Index-International (DQI-I) was used to evaluate the plans across dimensions of variety, adequacy, moderation, and balance. Caloric accuracy was analysed by calculating percentage deviations from requested targets and categorising discrepancies into defined ranges. Results: All chatbots achieved high total DQI-I scores (DQI-I > 70), demonstrating satisfactory overall diet quality. However, balance sub-scores related to macronutrient and fatty acid distributions were consistently the lowest, showing a critical limitation in AI algorithms. ChatGPT 4.0 exhibited the highest precision in caloric adherence, while Gemini showed greater variability, with over 50% of its diet plans deviating from the target by more than 20%. Conclusions: AI-driven chatbots show significant promise in generating nutritionally adequate and diverse weight-loss diet plans. Nevertheless, gaps in achieving optimal macronutrient and fatty acid distributions emphasise the need for algorithmic refinement. While these tools have the potential to revolutionise personalised nutrition by offering precise and inclusive dietary solutions, they should enhance rather than replace the expertise of dietetic professionals.

Keywords: AI technology; caloric accuracy; chatbots; diet quality; personalised nutrition; weight-loss diets.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Methodological framework for assessing chatbot-generated diet plans.
Figure 2
Figure 2
Bar charts of mean total DQI-I scores and sub-scores for Gemini, Microsoft Copilot, and ChatGPT 4.0.
Figure 3
Figure 3
Distribution of diet plans by percentage difference between requested and generated calorie levels.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

References

    1. Alowais S.A., Alghamdi S.S., Alsuhebany N., Alqahtani T., Alshaya A.I., Almohareb S.N., Aldairem A., Alrashed M., Bin Saleh K., Badreldin H.A., et al. Revolutionizing healthcare: The role of artificial intelligence in clinical practice. BMC Med. Educ. 2023;23:689. doi: 10.1186/s12909-023-04698-z. - DOI - PMC - PubMed
    1. Lee D., Yoon S.N. Application of Artificial Intelligence-Based Technologies in the Healthcare Industry: Opportunities and Challenges. Int. J. Environ. Res. Public Health. 2021;18:271. doi: 10.3390/ijerph18010271. - DOI - PMC - PubMed
    1. Dwivedi Y.K., Hughes L., Ismagilova E., Aarts G., Coombs C., Crick T., Duan Y., Dwivedi R., Edwards J., Eirug A., et al. Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. Int. J. Inf. Manag. 2021;57:101994. doi: 10.1016/j.ijinfomgt.2019.08.002. - DOI
    1. Johnson K.B., Wei W.Q., Weeraratne D., Frisse M.E., Misulis K., Rhee K., Zhao J., Snowdon J.L. Precision Medicine, AI, and the Future of Personalized Health Care. Clin. Transl. Sci. 2021;14:86–93. doi: 10.1111/cts.12884. - DOI - PMC - PubMed
    1. Morgan-Bathke M., Raynor H.A., Baxter S.D., Halliday T.M., Lynch A., Malik N., Garay J.L., Rozga M. Medical Nutrition Therapy Interventions Provided by Dietitians for Adult Overweight and Obesity Management: An Academy of Nutrition and Dietetics Evidence-Based Practice Guideline. J. Acad. Nutr. Diet. 2023;123:520–545.e510. doi: 10.1016/j.jand.2022.11.014. - DOI - PubMed

Publication types

LinkOut - more resources