A deep neural network approach to predicting clinical outcomes of neuroblastoma patients
Background: The availability of high-throughput omics datasets from large patient cohorts has allowed the development of methods that aim at predicting patient clinical outcomes, such as survival and disease recurrence. Such methods are also important to better understand the biological mechanisms u...
Saved in:
Main Authors: | Tranchevent, Léon-Charles, Azuaje, Francisco, Rajapakse, Jagath Chandana |
---|---|
Other Authors: | School of Computer Science and Engineering |
Format: | Article |
Language: | English |
Published: |
2021
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/146977 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Network-based integration of multi-omics data for clinical outcome prediction in neuroblastoma
by: Wang, Conghao, et al.
Published: (2023) -
Predicting clinical outcome of neuroblastoma patients using an integrative network-based approach
by: Rajapakse, Jagath Chandana, et al.
Published: (2018) -
Embedding Symbolic Knowledge into Deep Networks
by: Yaqi Xie, et al.
Published: (2020) -
DEEP NEURAL NETWORKS
by: BENJAMIN FRANCK CHRISTOPHE SCELLIER
Published: (2015) -
FORECASTING BITCOIN PRICES USING DEEP LEARNING AND MACHINE LEARNING
by: PANKHURI AGGARWAL
Published: (2021)