Predicting Quality of Life in Parkinson's Disease: A Machine Learning Approach Employing Common Clinical Variables.

ABSTRACT: Background: Parkinson's Disease significantly impacts health-related quality of life, with the Parkinson's Disease Questionnaire-39 extensively used for its assessment. However, predicting such outcomes remains a challenge due to the subjective nature and variability in patient experiences. This study develops a machine learning model using accessible clinical data to enable predictions of life-quality outcomes in Parkinson's Disease and utilizes explainable machine learning techniques to identify key influencing factors, offering actionable insights for clinicians. Methods: Data from the Parkinson's Real-world Impact Assessment study (PRISM), involving 861 patients across six European countries, were analyzed. After excluding incomplete data, 627 complete observations were u

SUBMITTER: Magano D 

PROVIDER: S-EPMC11396193 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature