Visual Inspection Hybrid System for Vitamin-D Deficiency

Vitamin D deficiency is a common health problem, but current blood tests for diagnosis are often too expensive and invasive, especially in places with limited resources. To solve this, this project is creating a new, easy-to-use screening tool that is not invasive. Our approach is to use advanced AI, like deep learning models (CNNs), to analyze visual cues from multiple body parts (like the face, nails, hair, and tongue) and combine this with information about a person's sun exposure and diet. This method aims to provide a more accurate, accessible, and comprehensive way to detect Vitamin D deficiency early, making it easier to manage this widespread health issue.