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Our final project purpose to examine the impact of Surgeon and Hospital Procedural Volume on Outcomes after CABG procedure .
Bins.py - Divided each line of yearly experience to bins.
GLMM.py - GLMM python model.
Plots_trend.py - Generates our various plots depends on selected experience.
Reop SHAP output.py - Run the final models on Reop Data and generates confusion matrix and SHAP plots.
RetrainModelComplics.py - Retrain model for Complication models.
RetrainModels.py - Retrain model for Mortality models.
SHAP output.py - Run the final models and generates confusion matrix and SHAP plots.
SelectedYears.py - generates summaries tables of the experience of selected target variable.
tables.py - create six tables with analysis. each type of mortality : 'total_surgery_count', 'total_CABG', 'Reop'
with each outcome: 'Mortalty', 'Complics'. The data for creating the tables is in Tables directory.
and its name is HospID/surgid+'_allyears_expec_surgid_STSRCOM.csv'
Tables dir - Contains all the data we used on the various scripts.
ClusterFiles - Script that we run on cluster, for grid search and SMOTE SHAP outputs.
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