Authors : Himani Kalra; Vishal Sugur; Karthick T

Volume/Issue : Volume 9 - 2024, Issue 5 - May

Google Scholar : https://tinyurl.com/ujd5dzj

Scribd : https://tinyurl.com/n3ked4u8

DOI : https://doi.org/10.38124/ijisrt/IJISRT24MAY395

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : With the advent of smart processing systems in computers it has driven the emergence of inventive solutions within health-care. One notable instance is the Skin Disease Detection and Recommendation System, utilizing AI and machine learning methods to elevate dermatological diagnosis and treatment guidance. This summary offers a comprehensive overview of the Skin Disease Detection System, outlining its core elements, methodologies, advantages, and potential healthcare impact. The System for Skin Disease Detection aims to transform dermatology by automating the skin disease identification process and delivering customized treatment suggestions. This also aims to detect the skin types and suggest remedial medication and other things for the same. Consulting with a dermatologist is also easy by this. Employing image processing, pattern recognition, and deep learning algorithms, this system accurately evaluates skin condition images. The solution's application was developed using Streamlit, Python, PHP, Bootstrap, and MySQL.

Keywords : Skin-Disease Prediction, Deep Learning, Responsive-Web-Design, Efficient Net, Streamlit, Database Management System, Data Security, Scalability, Responsive Load-Balancing, Increased Product.

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