Vitamin Deficiency Detection Using Image Processing and Neural Network

Abstract

This review examines recent advances in vitamin deficiency detection using free artificial intelligence (AI)-based web applications focusing on non-invasive methods including and imaging and convolutional neural analysis of specific body parts, such as eyes, lips, tongue, and nails Networks (CNNs) are used Traditional methods often involve expensive lab tests, whereas application provided enables individuals to identify themselves as potential vitamin deficiencies by sending images Intelligent software trained to recognize specific symp- toms in selected body parts indicating nutritional deficiencies in. This approach aims to address global health concerns through early nutrient identification and improved nutritional literacy. Potential benefits include initial screening, personalized recom- mendations, and health decision support. Overall, this technology addresses the critical need for timely and easy detection of vitamin deficiencies, thereby improving global health outcomes. Index terms — vitamin deficiency, image processing, CNN, web application, fuzzy algorithm.