DeepBTS: Prediction of Recurrence-free Survival of Non-small Cell Lung Cancer Using a Time-binned Deep Neural Network

Accurate prediction of non-small cell lung cancer (NSCLC) prognosis after surgery remains challenging. The Cox proportional hazard (PH) model is widely used, however, there are some limitations associated with it. In this study, we developed novel neural network models called binned time survival an...

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Detalles Bibliográficos
Autores principales: Lee, Bora, Chun, Sang Hoon, Hong, Ji Hyung, Woo, In Sook, Kim, Seoree, Jeong, Joon Won, Kim, Jae Jun, Lee, Hyun Woo, Na, Sae Jung, Beck, Kyongmin Sarah, Gil, Bomi, Park, Sungsoo, An, Ho Jung, Ko, Yoon Ho
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7005286/
https://www.ncbi.nlm.nih.gov/pubmed/32029785
http://dx.doi.org/10.1038/s41598-020-58722-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7005286/
https://www.ncbi.nlm.nih.gov/pubmed/32029785
http://dx.doi.org/10.1038/s41598-020-58722-z

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