Empirical approach to classification of individuals with chronic pain to optimize multimodal pain rehabilitation

Chronic pain is associated with a wide range of negative consequences. Given recognized heterogeneity of individuals with chronic pain in terms of clinical characteristics, presentation and functioning, decisions about the classification of individuals with pain have significant scientific and clinical implications.

In the context of machine learning, the goal of this project is to use advanced data-driven methods to classify individuals into discrete subgroups with high clinical utility in order to optimize and improve treatment selection and personalization in multidisciplinary treatment using data from the National Quality Registry for Pain Rehabilitation (NRS).