VITAMIN DEFICIENCY DETECTION USING IMAGE PROCESSING AND NEURAL NETWORK

Vitamin deficiencies result in physical health problems which attack nails and tongues and skins of people globally. When medical practitioners identify vitamin deficiencies they should activate early diagnostic methods to enable adequate preventive actions and treatment approaches. A machine learning system uses pictures of nail and tongue and skin defects to forecast vitamin deficiency cases. This system evaluates anomalies through neural network analysis of Convolutional Neural Networks (CNN) along with MobileNet and Long Short-Term Memory (LSTM) networks that function across various deep learning depth levels at the top position where MobileNet serves as the hybrid model.The project consists mainly of an analysis component for nail and tongue pictures alongside a classification part for skin problems