AI-Driven Personalized Health & Nutrition Assistant Using DeepSeek and LLaVA

Authors

  • S.V. Evangelin Sonia
  • Jebakumari Sutha.A
  • V Nisha
  • Sylvia Joice. M.J
  • Charles Finney Andrews D
  • Sebin Sunny
  • G. Naveen Sundar

DOI:

https://doi.org/10.52783/jns.v14.2734

Keywords:

N/A

Abstract

Traditional medical care failed to provide the personalized individualized analysis which makes it hard to get individualised wellness advice. Artificial intelligence writes down data analysis to personalize health advice from intelligent systems that solves the problem of simply giving general health care advice. According to this project, DeepSeek is coming together with LLaVA in order to develop better AI-based nutrition and wellness guidance. Users can access structured profiles containing BMI measurements, diet patterns, physical exercise, and medical health conditions (such as pressure) as well as stress monitoring, which will allow reaching an exact health recommendation. The LLaVA reads text and images simultaneously to precisely analyze what is being said through the DeepSeek system that provides relevant health guidance to users. Using the Flask based backend with real time AI and the ability to monitor the health status of the continuous data by providing class authentication. We have developed the AI solution in a manner that seamlessly binds well with Flutter frontends to propel accessibility forward while jumpering the users’ engagement by way of offering tailored and mass healthcare guidance. It applies an advanced structure that will adopt the developing platform of health oriented AI technology.

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Published

2025-03-28

How to Cite

1.
Sonia SE, Sutha.A J, Nisha V, M.J SJ, Andrews D CF, Sunny S, et al. AI-Driven Personalized Health & Nutrition Assistant Using DeepSeek and LLaVA. J Neonatal Surg [Internet]. 2025 Mar. 28 [cited 2026 Feb. 10];14(9S):668-74. Available from: https://jneonatalsurg.com/index.php/jns/article/view/2734