2.6. Data analysis
We used MySQL and Tableau (version 2019.1.0) to extract data from
MIMIC-III v1.4, and Python3.7 to build models and process data. The
working environment was PyCharm 2018.3.2.
Each of machine learning models involves a parameter-tuning process, so
we used the learning curve and grid search to select the parameters to
get the best model (Table A.1 in Appendices). In this study, accuracy
rate, precision rate (P), recall rate (R), F1 score, and area under ROC
curve (AUROC) were used to measure the model performance.