• Dr. D. J. Nagendra Kumar
• Jagarlamudi Parameswari
• Gubbala Sai Prabha Madhuri
• Kotti Leela Tirumal
• Kantheti Subbi Ram Kumar

Vitamin deficiencies are a global health concern, leading to various health complications that often present visible symptoms in nails, tongue, and skin. Early detection of these deficiencies is crucial for effective treatment and prevention. This project aims to develop a machine learning-based system that predicts potential vitamin deficiencies by analyzing visual abnormalities observed in nail, tongue, and skin images. The system leverages state-of-the-art deep learning models, including Convolutional Neural Networks (CNN), MobileNet, and a hybrid modelcombining Long Short-Term Memory (LSTM) networks with MobileNet, to classify these abnormalities.

"CNN Based Image Analysis for Vitamin Deficiency Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 3, page no.d657-d672, March-2025, Available :http://www.jetir.org/papers/JETIR2503373.pdf

"CNN Based Image Analysis for Vitamin Deficiency Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 3, page no. ppd657-d672, March-2025, Available at : http://www.jetir.org/papers/JETIR2503373.pdf