Personalized prediction of depression in patients with newly diagnosed Parkinson's disease: A prospective cohort study

Depressive disturbances in Parkinson's disease (dPD) have been identified as the most important determinant of quality of life in patients with Parkinson's disease (PD). Prediction models to triage patients at risk of depression early in the disease course are needed for prognosis and stratification of participants in clinical trials. One machine learning algorithm called extreme gradient boosting (XGBoost) and the logistic regression technique...