Empowering Dermatology: A Web-based Approach to Skin Cancer Classification

Skin cancer detection is crucial for timely treatment, yet existing methods often lack efficiency and reliability. This study proposes an enhanced image classification model using Mobile Net architecture, leveraging advanced expert systems and deep learning techniques. Building upon previous research, we address limitations by training the model on the HAM10000 dataset and employing transfer learning with TensorFlow. Our approach achieves a remarkable accuracy of 95.7% in identifying various skin lesions, promising significant improvements in early detection. By automating detection and ensuring privacy through local data processing, our system aids dermatologists in making informed decisions, enhancing healthcare efficiency and patient outcomes. While challenges like optimization persist, our research highlights the potential of advanced technologies in addressing critical medical concerns, aiming to advance dermatological diagnostics and improve healthcare.