Disrupting Dermatology with Deep Learning
Viktor will go through the current challenges of dermatology, and how deep learning could contribute to their solution. He will introduce SkinScanner, a deep learning algorithm for universal skin disease image classification. He will demonstrate how transfer learning can be used to train a skin disease classification algorithm, whose cross-validation accuracy is close to trained human-eye performance. He will also share the long-term vision on how deep learning technologies could be used to automate diagnosis of skin diseases.
Viktor is co-founder of SkinScanner, a London-based startup specialized in using Deep Learning algorithms for skin conditions image classification. SkinSkanner’s ambition is to disrupt dermatology by making the early diagnosis of skin conditions quicker, cheaper and more accurate. Viktor holds a Master’s Degree from SciencesPo, Paris and is a member of CFA Institute. Viktor is a full stack developer with several years of med-tech experience, having launched a number of mobile and desktop-based applications in the healthcare space.