Vitamin Deficiency Detection System
Year: 2025
Type: article
Abstract: 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.
Authors: Janhavi Avinash Khune, Saniya Ajay Shiradkar, Tejas Pravin Admane, Vidhi Dilip Kumar Nimje, Dr. Nitin S. More
Institution: MIT Art, Design and Technology University
Language: English
Subfield: Health Information Management
Field: Health Professions
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W6949351303
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