9th International Conference on ICT for Sustainable Development

Authors - Sneha Rajendra Jadhav, Shabana Pirjade, Vinodkumar Bhutnal, Lakhan Rathod, Sonali Jagdale, Janvi Naik
Abstract - Skin diseases may have a detrimental effect on an individual's quality of life and can be difficult to diagnose and treat because of the lack of adequate medical resources. The skin is an essential organ that protects the body from environmental hazards. With a focus on early detection and efficient treatment, this research combines deep learning with image processing to provide a framework for accurate skin disease diagnosis. Skin condition classification is made easier by the use of cutting-edge methods such as the CNN model's DenseNet layers and VGG-19 for analyzing real-time picture data. Using sophisticated picture processing, the method makes illness symptoms visible and allows for early detection. As it guides healthcare activities proactively, the system creates customized recommendations for diagnosis-based treatments and preventative measures. This work greatly enhances healthcare outcomes by using technology to intervene promptly and to diagnose skin diseases more accurately and easily. Reducing negative effects on people's lives and promoting improvements in dermatological procedures and medical results are among the revolutionary possibilities. The ability to handle skin diseases holistically is demonstrated by this innovative approach.