Improving predictive models of glaucoma severity by incorporating quality indicators

Results showed that classification modelling is not negatively affected by the inclusion of less reliable tests in the training process. This means that less reliable tests do not subtract useful information from a model trained using only completely reliable data. Future work will be devoted to exploring new quantitative thresholds to ensure high quality testing and low re-test rates. This could assist doctors in tuning patient follow-up and therapeutic plans, possibly slowing down disease progression.