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

PaoJen Kuo | Zendy; ShaoChun Wu | Zendy; PengChen Chien | Zendy; Shu-Shya Chang | Zendy; ChengShyuan Rau | Zendy; Hsueh-Ling Tai | Zendy; Shu-Hui Peng | Zendy; YiChun Lin | Zendy; YiChun Chen | Zendy; Hsiao-Yun Hsieh | Zendy; ChingHua Hsieh | Zendy

Open Access

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

Author(s) -

PaoJen Kuo,

ShaoChun Wu,

PengChen Chien,

Shu-Shya Chang,

ChengShyuan Rau,

Hsueh-Ling Tai,

Shu-Hui Peng,

YiChun Lin,

YiChun Chen,

Hsiao-Yun Hsieh,

ChingHua Hsieh

Publication year - 2018

Publication title -

oncotarget

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.373

H-Index - 127

ISSN - 1949-2553

DOI - 10.18632/oncotarget.24468

Subject(s) - medicine , logistic regression , surgery , head and neck cancer , neurosurgery , radiation therapy

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 logistic regression (LR).

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