Each year in the United States, over 5.4 million cases of nonmelanoma skin cancer are treated. Fortunately, skin cancer is the easiest cancer to cure if diagnosed and treated early; however, early detection is not always easy. The aim of this project was to develop a solution for early skin cancer detection that is readily available to 70%-80% of smart phones users. derML is a mobile application developed for the Android platform that uses machine learning and image recognition technology with Google’s TensorFlow framework to find patterns in pictures of skin moles, lesions, or other anomalies. The intent is for the algorithms to accurately predict if a given image of a skin anomaly is cancerous or benign and deliver that information to the user through an easy-to-use app.
JMU Undergraduate Student, James Madison University, ISAT
Joy Williams is a senior at James Madison University and will graduate with an Integrated Science and Technology degree with a concentration in Information and Knowledge Management. She is passionate about finding new ways to integrate machine learning in different softwares to help... Read More →