Skin cancer is a dangerous and widespread disease, and early detection increases the survival rate. It is found that a skilled dermatologist usually follows a series of steps, starting with the naked-eye observation of suspected lesions, then dermoscopy followed by biopsy. This would consume time and the disease may advance to later stages. Moreover, accurate diagnosis is subjective, depending on the skill of the clinician. In order to diagnose skin cancer speedily at the earliest stage, we need extensive research solutions by developing computer image analysis algorithms. We have come up with an AI-Based Solution Compliance for predictive modeling and diagnosis of Skin Cancer disease.

The entire solution is divided into four parts:

1. Trained Neural Network to predict disease and its stage ‘Benign or Malignant’.
2. Web-based frontend framework UI for users (patient).
3. Geotagging of potential patients and referring them to the nearest doctor along with other information.
4. Chatbot to assist users with diagnosis from the app and answer skin cancer related queries.