Survival Analysis with High-Dimensional Omics Data Using a Threshold Gradient Descent Regularization-Based Neural Network Approach

Analysis of data with a censored survival response and high-dimensional omics measurements is now common. Most of the existing analyses are based on specific (semi)parametric models, in particular the Cox model. Such analyses may be limited by not having sufficient flexibility, for example, in accom...

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Detalles Bibliográficos
Autores principales: Fan, Yu, Zhang, Sanguo, Ma, Shuangge
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9498566/
https://www.ncbi.nlm.nih.gov/pubmed/36140842
http://dx.doi.org/10.3390/genes13091674

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9498566/
https://www.ncbi.nlm.nih.gov/pubmed/36140842
http://dx.doi.org/10.3390/genes13091674

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