Artificial Intelligence-Based Diet: An Interventional Field Study

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  • Department of Primary Health Care, Sevamob Ventures Limited, Lucknow, Uttar Pradesh - 226 001 ,IN



Artificial Intelligence, Diet, Field Trial, Dietician.


Specialist dieticians and nutritionist are not present in every hospital of developing countries like India, where malnutrition and metabolic diseases are a big problem. Use of Artificial Intelligence (AI) to prepare a diet chart may be an answer to this problem. Pre-post analytic observational field study was done at multiple centres to evaluate and compare AI based diet accuracy with the diet advised by the dieticians. Accuracy of the Diet AI in providing counseling to the patients for improvements in nutritional choices and lifestyle was found to be high at 96%. The AI based diet plan can overcome the need of expert dieticians at remote hospitals and rural areas where trained dieticians are not available.


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How to Cite

Agrawal, A. (2020). Artificial Intelligence-Based Diet: An Interventional Field Study. The Indian Journal of Nutrition and Dietetics, 57(3), 240–253.



Original Articles
Received 2020-03-31
Accepted 2020-06-17
Published 2020-07-30



Pal, A., Pari, A.K., Sinha, A. and Dhara, P.C. Prevalence of under nutrition and associated factors: A cross-sectional study among rural adolescents in West Bengal, India. Int. J. Pediat. Adolescent Med., 2017, 4, 9-18. DOI:

Meenakshi, J. V. Trends and patterns in the triple burden of malnutrition in India. Agricul. Econom., 2016, 47, 115-134. DOI:

Thow, A.M., Kadiyala, S., Khandelwal, S., Menon, P., Downs, S. and Reddy, K.S. Toward food policy for the dual burden of malnutrition: An exploratory policy space analysis in India. Fd. Nutr. Bull., 2016, 37, 261-274. DOI:

Ackerson, L. K. and Subramanian, S. V. Domestic violence and chronic malnutrition among women and children in India. Am. J. Epidemiol., 2008, 167, 1188-1196. doi:10.1093/aje/kwn049. DOI:

Yount, Kathryn M., Digirolamo, Ann M., Ramakrishnan and Usha. Impacts of domestic violence on child growth and nutrition: A conceptual review of the pathways of influence. Social Sci. Med., 2011, 72, 1534-1554. doi:10.1016/j.socscimed.2011.02.042. DOI:

Goyache, F., Bahamonde, A., Alonso, J., López, S., Coz, J.J., Quevedo, J.R., Ranilla, J., Luaces, O., ílvarez, I.G., Royo, L.J. and Dí­ez, J. The usefulness of artificial intelligence techniques to assess subjective quality of products in the food industry. Trends in Fd. Sci. Technol., 2001, 12, 370-381. DOI:

Tandon, N., Anjana, R.M., Mohan, V., et al. The increasing burden of diabetes and variations among the states of India: the Global Burden of Disease Study 1990-2016. Lancet Glob. Health., 2018, 6, 1352-1362.

Anchala, R., Kannuri, N.K., Pant, H., Khan, H., Franco, O.H., Di Angelantonio, E., Emanucle Di Angelantonio and Dorairaj Prabhakaran. Hypertension in India: A systematic review and meta-analysis of prevalence, awareness, and control of hypertension. J. Hypertens., 2014, 32, 1170-1177. DOI:

Rekha Kumari, Raushan Kumar Bharti, Kalpana Singh, Archana Sinha, Sudhir Kumar, Anand Saran, Uday Kumar. Prevalence of iron deficiency and iron deficiency anaemia in adolescent girls in a tertiary care hospital. J. Clin. Diagn. Res., 2017, 11, 04-06. DOI:

Fox, R. and Bui, Y. An artificial intelligence approach to nutritional meal planning for cancer patients. In: Silhavy R., Senkerik R., Oplatkova Z., Prokopova Z., Silhavy P. (eds) Artificial Intelligence Perspectives and Applications. Advances in Intelligent Systems and Computing, 2015, 347. Springer, Cham.