Development and Validation of a Personalized Survival Prediction Model for Uterine Adenosarcoma: A Population-Based Deep Learning Study

BACKGROUND: The aim was to develop a personalized survival prediction deep learning model for adenosarcoma patients using the surveillance, epidemiology and end results (SEER) database. METHODS: A total of 797 uterine adenosarcoma patients were enrolled in this study. Duplicated and useless variable...

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Detalles Bibliográficos
Autores principales: Qu, Wenjie, Liu, Qingqing, Jiao, Xinlin, Zhang, Teng, Wang, Bingyu, Li, Ningfeng, Dong, Taotao, Cui, Baoxia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Oncology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7930479/
https://www.ncbi.nlm.nih.gov/pubmed/33680946
http://dx.doi.org/10.3389/fonc.2020.623818

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7930479/
https://www.ncbi.nlm.nih.gov/pubmed/33680946
http://dx.doi.org/10.3389/fonc.2020.623818

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