A Design of Polygenic Risk Model with Deep Learning for Colorectal Cancer in Multiethnic Indonesians

被引：3

作者：

Amadeus, Steven ^{[1
]}

Cenggoro, Tjeng Wawan ^{[2
,3
]}

Budiarto, Arif ^{[2
,3
]}

Pardamean, Bens ^{[1
,3
]}

机构：

[1] Bina Nusantara Univ, Comp Sci Dept, BINUS Grad Program, Master Comp Sci Program, Jakarta 11480, Indonesia

[2] Bina Nusantara Univ, Sch Comp Sci, Comp Sci Dept, Jakarta 11480, Indonesia

[3] Bina Nusantara Univ, Bioinformat & Data Sci Res Ctr, Jakarta 11480, Indonesia

来源：

5TH INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND COMPUTATIONAL INTELLIGENCE 2020 | 2021年 / 179卷

关键词：

Prognostication; Polygenic Risk Model; Transformer Model; DeepLIFT; Colorectal Cancer;

D O I：

10.1016/j.procs.2021.01.049

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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. (C) 2021 The Authors. Published by Elsevier B.V.

引用

页码：632 / 639

页数：8

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