Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{179447,
        author = {Ajay.S and Pradeep.P and Prabakar.K and PraveenKumar.P},
        title = {Skin AI Our Pocket Dermatologist Ai Powered Diagnoses for Healthier Skin},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {7930-7936},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=179447},
        abstract = {Skin conditions affect millions globally,
yet access to timely and accurate dermatological
care remains limited. Traditional diagnosis
methods can be delayed and resource-intensive.
Our mobile app, SkinAI: Your Pocket
Dermatologist, leverages artificial intelligence to
provide instant, on-device skin disease predictions.
Users can capture skin images and receive realtime diagnoses powered by a trained convolutional
neural network (CNN). Results are presented
alongside educational insights and nearby
dermatology clinic suggestions via location-based
filtering. With TFLite integration and offline
capabilities, SkinAI offers accessible, private, and
fast skin assessments. Early trials indicate
enhanced skin health awareness and timely careseeking behavior. This article explores the
development and healthcare impact of SkinAI.},
        keywords = {SkinAI, dermatology, AI diagnosis, convolutional neural network, mobile health, skin disease detection, TFLite.},
        month = {May},
        }