Artificial Intelligence in Cosmetic- Dermatology

This paper presents an AI-driven prototype for personalized skincare and haircare product recommendation. The system integrates a rule-based chatbot interface with a structured product knowledge base in JSON format. Users interact via natural language, describing dermatological or hair-related concerns (e.g., oily skin, acne, dandruff), and receive relevant product suggestions based on keyword matching and routine detection. The chatbot is built using Python and deployed through a Gradio web interface, allowing both text and image input. Although image analysis is currently implemented as a placeholder, the framework is designed for future integration of deep learning models (e.g., CNNs) to classify skin and scalp conditions. This work lays the foundation for an accessible and extensible AI assistant in the domain of cosmetic dermatology. Future iterations will incorporate PyTorch-based convolutional neural networks for condition classification and real-time severity scoring. The prototype demonstrates the feasibility of combining structured knowledge and conversational AI for enhancing user self-care decisions in dermatology and trichology. Keywords—Artificial Intelligence, Skincare Recommender, Gradio Interface, Dermatological Chatbot, Natural Language Processing, Deep Learning Integration, Haircare Assistant.