Affiliation:
1. Anjuman College of Engineering and Technology, Nagpur, Maharashtra, India
Abstract
Skin cancer is one of the most growing types and dangerous cancer in the world. The early diagnosis of melanoma and other ski cancer is a critical issue for dermatologists. In this paper, we using Machine Learning Algorithm for Detection of Deadliest Forms of Skin Cancer. This project aims to develop a skin cancer detection ML Model which can classify the skin cancer types and help in early detection. The ML Model is developed in Dot Net (. Net). The model is developed and tested with different network architectures by varying the type of layers used to train the machine. Basically our model use DNN (Deep Neural Network) and ResNet50 for detection of skin cancer. The model will be tested and trained on the dataset collected from the International Skin Imaging Collaboration (ISIC)
Reference6 articles.
1. K. Korotkovand R. Garcia, “Computerized analysis of pigmented skin lesions: A review”, Artificial Intelligence in Medicine, 56 (2),2012,pp. 69–90.
2. J. Scharcanski, M. E. Celebi and S. Service, “Online. Computer Vision Techniques for the Diagnosis of Skin Cancer”, 2014, pp. 193–219.
3. L. Li, Q. Zhang, Y. Ding, H. Jiang, B. H. Thiers and J. Z. Wang, “Automatic diagnosis of melanoma using machine learning methods on a spectroscopic system”, BMC Medical Imaging, 14 (1),2014, 36
4. E. Barati, M. Saraee, A. Mohammadi, N. AdibiandM.R. Ahamadzadeh, “A Survey on Utilization of Data Mining Approaches for Dermatological (Skin) Diseases Prediction”, Journal of Selected Areas in Health Informatics, 2 (3),2011,pp. 1–11.
5. L. Perez and J. Wang, “The Effectiveness of Data Augmentation in Image Classification using Deep Learning,” Dec. 2017.