Natural language processing to measure communication between healthcare professionals and family members of critically ill patients
Files
01_webscraper.py: webscraper used to collect people's names from the internet
02_pre-processing.py: it includes all pre-processing and dataset construction methods
03_ML_approach_part1.py: stratified 10-fold cross-validation grid search for machine learning (logistic regression, support vector machine, random forest and adaptive boosting)
04_ML_approach_part2.py: stratified 10-fold cross-validation grid search for machine learning (neural network)
05_ML_approach_summary.py: it combines results from parts one and two and summarizes the best performing methods
06_RBC_approach.py: rule based classifier approach
auxiliar_data.xlsx: includes auxiliar information used by Python files
input_file.xlsx: shows an example of how the input file should be structured in order to be used with the Python files