Skin cancer is the most prevalent type of cancer. Melanoma, specifically, is responsible for 75% of skin cancer deaths, despite being the least common skin cancer. The American Cancer Society estimates over 100,000 new melanoma cases will be diagnosed in 2020. It’s also expected that almost 7,000 people will die from the disease. As with other cancers, early and accurate detection potentially aided by data science can make treatment more effective.
Leveraging the power of Deeplearning and Datascience, a solution is given to identify melanoma in images of skin lesions.
Experimented with different types of architecture to come up with a custom solution which boosted our base AUC from 0.91 to 0.93
Project link: https://github.com/RsTaK/Melonoma-Skin-Cancer-Detection