Development, Validation and Comparison of Artificial Neural Network Models and Logistic Regression Models Predicting Survival of Unresectable Pancreatic Cancer

Background: Prediction models for the overall survival of pancreatic cancer remain unsatisfactory. We aimed to explore artificial neural networks (ANNs) modeling to predict the survival of unresectable pancreatic cancer patients. Methods: Thirty-two clinical parameters were collected from 221 unrese...

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Detalles Bibliográficos
Autores principales: Tong, Zhou, Liu, Yu, Ma, Hongtao, Zhang, Jindi, Lin, Bo, Bao, Xuanwen, Xu, Xiaoting, Gu, Changhao, Zheng, Yi, Liu, Lulu, Fang, Weijia, Deng, Shuiguang, Zhao, Peng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Bioengineering and Biotechnology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7082923/
https://www.ncbi.nlm.nih.gov/pubmed/32232040
http://dx.doi.org/10.3389/fbioe.2020.00196

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7082923/
https://www.ncbi.nlm.nih.gov/pubmed/32232040
http://dx.doi.org/10.3389/fbioe.2020.00196

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