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...

Descripción completa

Detalles Bibliográficos
Autores principales: Tranchevent, Léon-Charles, Azuaje, Francisco, Rajapakse, Jagath C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6923884/
https://www.ncbi.nlm.nih.gov/pubmed/31856829
http://dx.doi.org/10.1186/s12920-019-0628-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6923884/
https://www.ncbi.nlm.nih.gov/pubmed/31856829
http://dx.doi.org/10.1186/s12920-019-0628-y

Ejemplares similares