Prognostically Relevant Subtypes and Survival Prediction for Breast Cancer Based on Multimodal Genomics Data

Cancer is one of the deadliest diseases caused by abnormal behaviors of genes that control the cell division and growth. Genomics data and clinical outcomes from multiplatform and heterogeneous sources are used to make clinical decisions for the cancer patients, where both multimodality and heteroge...

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Bibliographic Details
Published in:	IEEE access Vol. 7; p. 1
Main Authors:	Karim, Md. Rezaul, Wicaksono, Galih, Costa, Ivan G., Decker, Stefan, Beyan, Oya
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 01.01.2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Bioinformatics Breast cancer Cancer genomics Cancer subtype Cell division Decision trees Deoxyribonucleic acid DNA DNA methylation Estrogens Gene expression Genomics Growth factors Heterogeneity Machine learning Multimodal autoencoder Receptors Regression analysis Ribonucleic acid RNA Support vector machines Survival Survival prediction
ISSN:	2169-3536, 2169-3536
Online Access:	Get full text
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