International Journal on Science and Technology

E-ISSN: 2229-7677   •   Impact Factor: 9.88

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 16 Issue 2 April-June 2025 Submit your research before last 3 days of June to publish your research paper in the issue of April-June.
Submit Research Paper Join as a Reviewer

Plagiarism is checked by the leading plagiarism checker TurnItIn

Call for Paper

Volume 16 Issue 2
2025

Submit your research paper

Indexing Partners
Academia Advanced Sciences Index Bielefeld Academic Search Engine CiteSeer DRJI Google Scholar Independent Search Engine & Directory Network ISI (International Scientific Indexing) Issuu Mendeley Research Networks
RefSeek ResearcherId - Thomson Reuters ResearchGate Scirus Scribd Semantic Scholar UTeM - Universiti Teknikal Malaysia Melaka Wiki for Call for Papers WorldCat Zenodo

Vitamin Deficiency Detection Using Machine Learning And Deep Learning Algorithms

Author(s) S.Purushotham, S.Karthik Reddy, S.Bharath Kumar Reddy, MRS.V.Vidhya, DR.V. Sai Shanmuga Raja
Country India
Abstract Vitamin deficiencies are a significant global healthconcern, affecting millions across various age groups andgeographical regions. Deficiencies in essential vitamins canlead to a range of health issues, impacting overall physicalwell-being and quality of life. Early detection andappropriate management of vitamin deficiencies are crucialin mitigating these adverse effects. Recognizing the needfor accessible diagnostic tools and personalized nutritionalguidance, this project introduces a web-based applicationthat integrates machine learning to detect potential vitamindeficiencies and provide targeted vitaminrecommendations. Vitamin deficiencies can contribute tonumerous health conditions, affecting physical well-beingand quality of life. This project proposes a web-basedapplication that leverages machine learning to analyzespecific symptoms, such as skin tone, hair health, and skininflammation, associated with vitamin deficiencies, andprovides predictions for potential health conditions. Byallowing users to upload images or describe symptoms,the application predicts common deficiencies and offerstargeted vitamin recommendations to support better healthoutcomes. The primary goal of this project is to create anaccessible platform where individuals can submit theirhealth symptoms or relevant images and receiveimmediate predictions on possible conditions related tovitamin deficiencies. The platform is designed to providerecommendations for specific vitamins based on theirscientifically-established roles.
Keywords Cnn,deeplearning
Field Engineering
Published In Volume 16, Issue 2, April-June 2025
Published On 2025-04-07
Cite This Vitamin Deficiency Detection Using Machine Learning And Deep Learning Algorithms - S.Purushotham, S.Karthik Reddy, S.Bharath Kumar Reddy, MRS.V.Vidhya, DR.V. Sai Shanmuga Raja - IJSAT Volume 16, Issue 2, April-June 2025. DOI 10.71097/IJSAT.v16.i2.3346
DOI https://doi.org/10.71097/IJSAT.v16.i2.3346
Short DOI https://doi.org/g9drc6
View / Download PDF File

Share this



CrossRef

CrossRef DOI is assigned to each research paper published in our journal.

IJSAT DOI prefix is
10.71097/IJSAT

Downloads
Research Paper Format Copyright Permission Form and Undertaking Form Cover Page Vol 15 Isu 4Cover Page Vol 15 Isu 3Cover Page Vol 15 Isu 2

All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.

CC-BY-SA Open Access

About IJSAT
Fees & Payment
Current Issue
Publication Archive 		Submit Research Paper
Track Submission Status
Publication Guidelines
Publication Ethics
Peer Review & Plagiarism 		Join as a Reviewer
Editors & Reviewers
Reviewer Referral Program
Get Reviewer Membership Certi. 		Website/Journal Policies
Usage Policy
Content Policies
Privacy Policy
Contact Us Message on WhatsApp +91-9687-182-185 editor@ijsat.org