Systems as described herein can include diagnosing and treating patients with chronic conditions, such as chronic back pain. A transition to chronic pain can include brain adaptations that can carve the state of chronic pain. Additionally, pain characteristics, pain related disability, and responses to treatment can be at least partially determined by psychological factors and/or personality properties. Personalized management recommendations can be generated for individual chronic pain patients using an infrastructure and associated methodology monitors chronic pain patients and gathers a large amount of group data (e.g., phenotyping participants at various levels of depth: behavior, psychology, brain anatomy and function, genetics, etc.) and machine learning methods to generate individualized treatment recommendations that are updated and retooled based on the group data analyses and based on the specific subject's responses.
BIG DATA-DRIVEN PERSONALIZED MANAGEMENT OF CHRONIC PAIN