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NUTRITION APP FOR ANEMIA – NUTRIFE

Adhithi S, Ananya. R

Abstract


Anemia continues to affect millions of people worldwide, often going unnoticed until symptoms interfere with daily life. Nutrife is created as a compassionate, AI-enabled nutrition platform that helps individuals understand and manage their anemia risk through simple, personalized, and accessible tools. The system integrates BMI assessment, tailored diet planning, food nutrient analysis, and an intuitive chatbot that offers friendly, easy-to-understand guidance. By combining nutrition science with intelligent technologies such as medical image interpretation and natural language processing, Nutrife empowers users to take charge of their health without feeling overwhelmed by medical terminology or fragmented information. The platform serves as a supportive digital companion, promoting early awareness, healthier eating practices, and long-term wellbeing. Through its human-centered design and unified feature set, Nutrife addresses the limitations of existing health apps and offers a holistic approach to preventing and managing nutritional anemia.


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References


A. Sharma, B. Lee, and C. Zhang, "NutriAI: A Deep Learning Framework for Personalized Nutritional Anemia Management," IEEE J. Biomed. HealthInform., vol. 28, no. 5, pp. 2456–2464, May 2024.

K. Patel, S. Watanabe, and R. Kumar, "Real-Time Food Recognition and Micronutrient Analysis for Anemia Prevention," Sensors, vol. 24, no. 8, p. 2567,

Apr. 2024.

M. Al-Jarrah, T. Jones, and L. Chen, "A Federated Learning Approach for Privacy-Preserving Anemia Risk Prediction," in Proc. IEEE Big Data, 2024, pp. 1123–1128.

E. Rossi, P. Singh, and F. Nielsen, "IronCalc: A Non-Invasive Hemoglobin Estimation Tool Using AI," Comput. Biol. Med., vol. 178, p. 108642, Jun. 2024.

H. Kim, D. Garcia, and Y. Wang, "Integrating Dietary Patterns with Biomarkers for Nutritional Deficiency Detection," IEEE Access, vol. 12, pp. 78945–78956, Feb. 2025.

L. Müller, A. Costa, and S. Park, "AnemiaScreener: Conjunctival Pallor Analysis Using EfficientNet," IEEE Trans. Mobile Comput., early access, Jan. 2025.

C. Davis, R. Gupta, and M. Tanaka, "Personalized Meal Planning for Iron-Deficiency Anemia," J. Intell. Inf. Syst., vol. 62, no. 3, pp. 1345–1362, Sep. 2024.

S. Li, N. Agarwal, and P. Rossi, "Chatbot-Based Health Assessment for Nutritional Deficiencies," in Proc. IEEE GHTC, 2024, pp. 278–283.

Z. Ouyang, F. Martinelli, and B. Lee, "Machine Learning Models for Predicting Vitamin B12 Deficiency," Comput. Math. Methods Med., vol. 2024, Art. 5567891, Aug. 2024.

G. Thompson, H. Zhao, and I. Popov, "Blockchain for Health Record Management in Dietary Apps," IEEE IoT J., vol. 11, no. 9, pp. 15678–15689, Nov. 2024.


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