MSc-HealthInformatics-thesis

Online material for thesis "Using machine learning models developed with English data to predict improvement in patient-reported outcome measures (PROMs) in a cohort of Welsh patients undergoing joint-replacement surgery":

• .gitignore --> list of files created that have not been uploaded on Github

Code

This folder contains the scripts that have been used for producing the outputs of the thesis:

Functions

• 00_ProjectFunctions.R --> it contains custom-made functions

Data pre-processing

• 01_Preprocess_EnglishHips.R --> pre-processing of data from the English hip replacement dataset
• 01_Preprocess_EnglishKnees.R --> pre-processing of data from the English knee replacement dataset
• 01_Preprocess_WelshHips.R --> pre-processing of data from the English hip replacement dataset
• 01_Preprocess_WelshKnees.R --> pre-processing of data from the English knee replacement dataset

Supervised machine learning

• 02_ML_main_OHS.R --> Development/validation of models for predicting post-surgical achievement of OHS MCID in the hip replacement dataset
• 02_ML_main_EQVAS_hips.R --> Development/validation of models for predicting post-surgical achievement of EQ-VAS MCID in the hip replacement dataset
• 02_ML_main_OKS.R --> Development/validation of models for predicting post-surgical achievement of OKS MCID in the knee replacement dataset
• 02_ML_main_EQVAS_knees.R --> Development/validation of models for predicting post-surgical achievement of EQ-VAS MCID in the knee replacement dataset

Plotting

• 03_Summary_Plots.R --> Creation of plots for evaluation of models during development and test phases

supplementary_online_material

• Data Dictionary - Additional English Predictors.pdf --> Data dictionary for extra 21 predictors used in supplementary analysis
• Data Dictionary.pdf --> Data dictionary for all the variables used in the main analysis
• Tripod Checklist.pdf --> Checklist for assessing study's transparency

supervised-ML-certificates

Certificates of accomplishment of online courses in supervised machine learning. These were followed in order to undertake the training to carry out the MSc thesis project.