Artificial neural network approach to predict surgical site infection after free-flap reconstruction in patients receiving surgery for head and neck cancer

BACKGROUND: The aim of this study was to develop an effective surgical site infection (SSI) prediction model in patients receiving free-flap reconstruction after surgery for head and neck cancer using artificial neural network (ANN), and to compare its predictive power with that of conventional logi...

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Detalles Bibliográficos
Autores principales: Kuo, Pao-Jen, Wu, Shao-Chun, Chien, Peng-Chen, Chang, Shu-Shya, Rau, Cheng-Shyuan, Tai, Hsueh-Ling, Peng, Shu-Hui, Lin, Yi-Chun, Chen, Yi-Chun, Hsieh, Hsiao-Yun, Hsieh, Ching-Hua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2018
Materias:
Research Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5862614/
https://www.ncbi.nlm.nih.gov/pubmed/29568393
http://dx.doi.org/10.18632/oncotarget.24468

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5862614/
https://www.ncbi.nlm.nih.gov/pubmed/29568393
http://dx.doi.org/10.18632/oncotarget.24468

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