Deep-CLASS at ISIC Machine Learning Challenge 2018
This work addresses skin disease classification for medical diagnosis, but it appears incremental as it builds on prior team experience without major innovations.
The team tackled the classification of seven skin diseases using deep learning, achieving results in the ISIC 2018 challenge, though no specific numbers are provided.
This paper reports the method and evaluation results of MedAusbild team for ISIC challenge task. Since early 2017, our team has worked on melanoma classification [1][6], and has employed deep learning since beginning of 2018 [7]. Deep learning helps researchers absolutely to treat and detect diseases by analyzing medical data (e.g., medical images). One of the representative models among the various deep-learning models is a convolutional neural network (CNN). Although our team has an experience with segmentation and classification of benign and malignant skin-lesions, we have participated in the task 3 of ISIC Challenge 2018 for classification of seven skin diseases, explained in this paper.