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
April-June 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

An AI Powered Web Application for Skin Disease Detection

Author(s) GANTA POORNA RAMA CHANDRA, MYADAM VINAYAK, GADDAM YASHWANTH, KUKUNOORPALLI VIKASTEJA
Country India
Abstract This research paper presents the design of a web-based application with the objective of supporting early skin disease detection through the application of real-time image processing. Following a trained CNN model on a dermatology dataset, the system accepts as input user-upload images and provides diagnostic feedback through an interactive web-enabled interface. The paper presents the integration of AI with healthcare and image recognition and promotes accessibility, accuracy, and user-friendliness without specialist hardware or constant internet connectivity. A critical review of the current literature on AI-based medical diagnoses, identification of gaps in existing skin disease detection solutions, and description of proposed system design and implementation are provided. The proposed system is assessed using prediction accuracy, user interaction, and overall effectiveness of the diagnostic tool. The findings present the capability of this project to support the early detection and skin condition insight of acne, eczema, and psoriasis. The contribution to literature provides a web-enabled, ease-of-use, and low-cost solution for dermatological treatment using innovative web-centric technology.
Keywords Skin Disease Detection, Deep Learning, Flask, TensorFlow, Image Classification, Dermatology AI, Web Application, Healthcare Technology
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 16, Issue 2, April-June 2025
Published On 2025-05-02
DOI https://doi.org/10.71097/IJSAT.v16.i2.4447
Short DOI https://doi.org/g9hbr7
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