A Machine Learning-Based Prediction of Hospital Mortality in Patients With Postoperative Sepsis
Introduction: The incidence of postoperative sepsis is continually increased, while few studies have specifically focused on the risk factors and clinical outcomes associated with the development of sepsis after surgical procedures. The present study aimed to develop a mathematical model for predict...
Main Authors: | Ren-qi Yao, Xin Jin, Guo-wei Wang, Yue Yu, Guo-sheng Wu, Yi-bing Zhu, Lin Li, Yu-xuan Li, Peng-yue Zhao, Sheng-yu Zhu, Zhao-fan Xia, Chao Ren, Yong-ming Yao |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2020-08-01
|
Series: | Frontiers in Medicine |
Subjects: | |
Online Access: | https://www.frontiersin.org/article/10.3389/fmed.2020.00445/full |
Similar Items
-
Epidemiological characteristics of postoperative sepsis
by: Chen Po-Yi, et al.
Published: (2019-12-01) -
Changes of non-specific resistance in patients with postoperative peritonitis with abdominal sepsis
by: M. M. Droniak
Published: (2021-03-01) -
Comparative analysis and prediction of nucleosome positioning using integrative feature representation and machine learning algorithms
by: Guo-Sheng Han, et al.
Published: (2021-06-01) -
Predicting Hard Rock Pillar Stability Using GBDT, XGBoost, and LightGBM Algorithms
by: Weizhang Liang, et al.
Published: (2020-05-01) -
Transparency Estimation of Narrow Rivers by UAV-Borne Hyperspectral Remote Sensing Imagery
by: Lifei Wei, et al.
Published: (2020-01-01)