Novel prognostication of patients with spinal and pelvic chondrosarcoma using deep survival neural networks

BACKGROUND: We used the Surveillance, Epidemiology, and End Results (SEER) database to develop and validate deep survival neural network machine learning (ML) algorithms to predict survival following a spino-pelvic chondrosarcoma diagnosis. METHODS: The SEER 18 registries were used to apply the Risk...

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Detalles Bibliográficos
Autores principales: Ryu, Sung Mo, Seo, Sung Wook, Lee, Sun-Ho
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6945432/
https://www.ncbi.nlm.nih.gov/pubmed/31907039
http://dx.doi.org/10.1186/s12911-019-1008-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6945432/
https://www.ncbi.nlm.nih.gov/pubmed/31907039
http://dx.doi.org/10.1186/s12911-019-1008-4

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