 |
|
Deep learning for stage prediction in neuroblastoma using gene expression data
Aron Park, Seungyoon Nam
Genomics Inform. 2019;17(3):e30 Published online 2019 Sep 27 DOI: https://doi.org/10.5808/GI.2019.17.3.e30
|
|
Citations to this article as recorded by
 Predicting Neuroblastoma Patient Risk Groups, Outcomes, and Treatment Response Using Machine Learning Methods: A Review
Leila Jahangiri
Medical Sciences.2024; 12(1): 5. CrossRef A multi-omics approach for biomarker discovery in neuroblastoma: a network-based framework
Rahma Hussein, Ahmed M. Abou-Shanab, Eman Badr
npj Systems Biology and Applications.2024;[Epub] CrossRef Enhancing the prediction of IDC breast cancer staging from gene expression profiles using hybrid feature selection methods and deep learning architecture
Akash Kishore, Lokeswari Venkataramana, D. Venkata Vara Prasad, Akshaya Mohan, Bhavya Jha
Medical & Biological Engineering & Computing.2023; 61(11): 2895. CrossRef Joint triplet loss with semi-hard constraint for data augmentation and disease prediction using gene expression data
Yeonwoo Chung, Hyunju Lee
Scientific Reports.2023;[Epub] CrossRef A Deep-Learning Model With the Attention Mechanism Could Rigorously Predict Survivals in Neuroblastoma
Chenzhao Feng, Tianyu Xiang, Zixuan Yi, Xinyao Meng, Xufeng Chu, Guiyang Huang, Xiang Zhao, Feng Chen, Bo Xiong, Jiexiong Feng
Frontiers in Oncology.2021;[Epub] CrossRef Neuroblastoma GD2 Expression and Computational Analysis of Aptamer-Based Bioaffinity Targeting
Godfred O. Sabbih, Michael K. Danquah
International Journal of Molecular Sciences.2021; 22(16): 9101. CrossRef
|