A Design of Polygenic Risk Model with Deep Learning for Colorectal Cancer in Multiethnic Indonesians
Recently, health management is emerging and attract attention to how to provide better prognostication and health management systems. The challenges in the prognostication are how to develop a model that can self-learn the prognostication features and how to get a high accuracy prediction. Prognostication in health disease involves SNPs which is a genetic marker. In this paper, we propose a polygenic risk model using deep learning: Transformer with self-attention mechanism and DeepLIFT. The use of these deep learning model allows us to predict the risk of colorectal cancer and see the correlation between SNPs.
International Conference on Computer Science and Computational Intelligence 2020
Steven Amadeus, Tjeng Wawan Cenggoro, Arif Budiarto, and Bens Pardamean
