Interpretable deep neural network for cancer survival analysis by integrating genomic and clinical data
Abstract Background Understanding the complex biological mechanisms of cancer patient survival using genomic and clinical data is vital, not only to develop new treatments for patients, but also to improve survival prediction. However, highly nonlinear and high-dimension, low-sample size (HDLSS) dat...
Main Authors: | Jie Hao, Youngsoon Kim, Tejaswini Mallavarapu, Jung Hun Oh, Mingon Kang |
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Format: | Article |
Language: | English |
Published: |
BMC
2019-12-01
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Series: | BMC Medical Genomics |
Subjects: | |
Online Access: | https://doi.org/10.1186/s12920-019-0624-2 |
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