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 modelling and diagnosis of Skin Cancer disease.
✔ Trained Neural Network to calculate and predict skin cancer alongwith the probability score on a single upload of image.
✔ Display the percentage of melignant and benign.
✔ Web based frontend framework UI for user (patient).
✔ Recommending the nearest doctors to the patient on single click of button.
✔ Human interacting both text and voice based chatbot to assist anyone who visits the website.
✔ Robust scalable and cross platform application that can be used on phone.
✔ Can be deployed on cloud as well as edge computer.
✔ Uses current location of patients to recommend nearest doctors.
✔ Trained using ResNet50 on an efficient dataset provided by International Skin Imaging Collaboration - Malonoma Project ISIC
✔ Comprehensive Profile of Doctors and Hospitals : Profile of doctors, hospital website, contact details, etc.
✔ Discussion Forums : Talk to experts, provide feedback, make appointments, etc.
✔ Dashboard for Patient’s History : Save Medical History of patients and doctors can see the progress there. So there would be no need to carry reports every time. Users be able to register and login into the application.