@ University of Tartu, Estonia
Deep Learning in Medicine and Computational Biology
Deep learning has been shown to be extremely successful in various domains from image and voice recognition to beating humans at playing games and sorting waste. A major part of this advancement is due to rich datasets available to researches in those domains. In biology the amount and the complexity of data has increased dramatically, over the past decade, making biology and medicine suitable domains for applying deep learning. At the beginning, applying even simple networks on these large amounts of biological data provided a sophisticated advantage over canonical machine learning methods. Now, new ideas were adapted from rapidly developing artificial intelligence field in order to improve the performance of deep learning models across various biological tasks, such as: genomics, medical diagnostics and biological image analysis. In this talk, we will review some of these major recent advances and discuss their potential impact on the field. The talk is based on a review paper – Computational biology – deep learning by William Jones, Kaur Alasoo, Dmytro Fishman et al. (accepted).