International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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

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AI-powered Skin Condition Analyzer with Personalized Skincare Recommendations

Author(s) Mr. MANJUNATHA G, Mr. Vinay Prakash, Ms. Yashaswini G D, Ms. Yashaswini R, Ms. Sharanya Sharanya
Country India
Abstract The progression of digital skincare imaging and virtual dermatology platforms calls for smart diagnostic systems that will be able to provide high accuracy, real-time processing, and personalized skincare guidance. The current article describes an AI-driven skin condition analysis system, which is built on the Python programming language and uses machine learning techniques—Convolutional Neural Network (CNN) for the highest precision feature extraction and Variational Autoencoder (VAE) for latent skin pattern analysis and condition classification. The system can reveal many skin problems, including acne, hyperpigmentation, uneven skin tone, pores, and texture irregularities, with an average diagnostic accuracy of 92%, gaining System scalability has been further verified on high-performance computing setups, achieving enhanced feature-mapping stability with a latent-space reconstruction accuracy of 93% and improved inference speed. Apart from diagnosis, the system embeds a personalized skincare recommendation engine that suggests next steps according to the conditions detected, skin sensitivity levels, and environmental factors.
Keywords AI Dermatology, Skin Analysis, Machine Learning, Deep Learning, Computer Vision, Face Analysis, Skincare Recommendation System, Personalized Beauty Tech
Field Engineering
Published In Volume 7, Issue 6, November-December 2025
Published On 2025-12-11
DOI https://doi.org/10.36948/ijfmr.2025.v07i06.62745
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E-ISSN 2582-2160
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