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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...
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 |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
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 |
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