Comprehensive Skin Disease Detection Using Ai

Comprehensive Skin Disease Detection Using Ai

Author Name : Mr. Galeebathullah B, S Priyadharshan Reddy, B Sai Likith, B Mourya, N Venkata Sundar

ABSTRACT : Skin ailments affect a considerable portion of the global populace, emphasizing the necessity for efficient and precise diagnostic aids. This study introduces an innovative approach for automated identification and categorization of diverse skin conditions through deep learning methodologies. Employing Convolutional Neural Networks (CNNs), the proposed system scrutinizes dermatological images to discern distinct patterns associated with various skin ailments. The primary aim is to provide a dependable and non-invasive diagnostic tool assisting dermatologists in clinical decision-making. Commencing with the assembly of a comprehensive dataset comprising images depicting a variety of skin diseases, meticulously labelled, the project progresses to train a custom deep neural network architecture on this dataset. This network learns to recognize intricate patterns and features indicative of different dermatological conditions. Rigorous evaluation, encompassing accuracy, precision, recall, and F1 score metrics, gauges the model's performance on an independent dataset. This research holds significance in potentially transforming dermatological diagnostics, offering a rapid and accurate means of identifying multiple skin diseases. By automating diagnosis, the proposed system expedites skin condition assessment and has the potential to enhance healthcare accessibility, particularly in regions with limited dermatological expertise. This endeavour aims to bridge the gap between conventional diagnostic methods and emerging technologies, ultimately improving patient outcomes, and advancing dermatological healthcare.