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Can machine learning models improve the prediction of surgical site infection in abdominal surgery than traditional statistical models?

 

Data Availability:
The data sets generated during analyses for this study are available from the corresponding author on reasonable request.
To request data, please complete online data request form (click here).

 

Codes:
Codes generated for the whole analyses are bellow.



Decision tree
Random Forest
XGBoost
Naive Bayes
Decision Tree

The Decision Tree model was created using Python version 3.7 and the codes were constructed as follows.

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Random Forest

The Random Forest model was created using Python version 3.7 and the codes were constructed as follows.

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XGBoost

The XGBoost model was created using Python version 3.7 and the codes were constructed as follows.

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Naive Bayes

The Naive Bayes model was created using Python version 3.7 and the codes were constructed as follows.

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Department of Clinical Epidemiology and Biostatistics