A Novel Model for Diagnosing the Cancerous Skin Diseases using Deep Learning Techniques

In order to predict, diagnose, monitor the disease in the field of dermatology, the traditional expertise leads loss of time and needs resource intensive. Identification and prediction of dermatological disease is prime important in present literature. The techniques of Generative AI (Gen AI) and Deep Learning (DL) plays a vital role from predicting to patient’s efficient outcomes. Some common things that affect skin are psychological impact, daily life impact, other disease treatment side effects, financial burden. To get an accurate and efficient results from early stage of identifying of skin disease, the techniques of DL such as Convolutional Neural Networks (CNN) will give high accuracy and reliability in image-based diagnostics. Long Short-Term Memory (LSTM) networks are very effective in predicting the diseases and modeling temporal and sequences in patients’ conditions. Added to the above, Gen AI will have more impact. Generative Adversarial Networks (GANs) will decrease the problem of limited datasets by generating high quality realistic images. The aim of the paper is to strengthen the image analysis, efficient workflow, predictive analysis, improved patient monitoring, increased training and realistic data generation.