Vitamin Deficiency Detection System

Vitamin deficiency has become a rampant worldwide health problem, associated with life-threatening complications like cardiovascular conditions, cancer, and immune disease. Conventional diagnosis is costly, invasive, and needs the expertise of the diagnostician. This paper presents a new, automated vitamin deficiency diagnostic system utilizing image processing and deep learning technology. Our method employs a CNN model trained from a database of annotated facial, skin, nail, and eye images to identify indicators of deficiencies. A minimalist web app permits users to upload images and provide real-time diagnostic feedback. The solution is inexpensive, scalable, and available, with controlled trials. The findings confirm the capability of AI-based image diagnosis as an addition to conventional methods and an advancement in accessible preventive healthcare.