Vitamin Deficiency Detection Using Image Processing and Neural Network

In this paper, a cost-free Artificial Intelligence-based application for smartphones built to detect vitamin deficiencies in humans using pictures of specific body organs is introduced. Recent vitamin deficiency detection methods require costly laboratory analysis. A wide spectrum of vitamin deficiencies can show one or more visually distinguishable symptoms and indications that appear in multiple locations in the human body. The application provides individuals with the capability to diagnose their possible vitamin deficiencies without the need to provide blood samples through the analysis of photos taken of their eyes, lips, tongue, and nails. The application then suggests a list of nutritional sources to fight the detected deficiency and the expected complications through nutritional micro-correction. The intelligent software was trained to distinguish and differentiate vitamin deficiencies with high confidence from imagery inputs of the selected body parts that are known to show different symptoms in terms of changes in the tissue's structure when the human body suffers a nutritional deficit. The platform also allows medical experts to assist in improving the range of detection and accuracy of the application through the contribution and verification of visual data of their patients allowing for more refined image analysis and feature extraction capabilities with the potential to surpass human's ability to diagnose medical conditions. This application is a useful tool for people to overcome a global problem that affects millions of people worldwide mainly as a result of inadequate nutritional awareness, and it will help healthcare workers in the long term in obtaining more accurate diagnoses.