The primary objective is to use machine learning methods on large survey and health register data to identify participants with different treatment trajectories and health outcomes after surgical and/or conservative treatment for spinal disorders. Secondary objectives are to 1) conduct external validation of the prediction models, and 2) explore how the prediction models can be implemented into AI-based clinical co-decision tools and interventions.
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AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
Patient-reported outcomes
Timeframe: depends upon the registry data, but in general between 2008 and 2022
Unfavourable outcomes
Timeframe: depends upon the registry data, but in general between 2008 and 2022
Prescribed medication
Timeframe: depends upon the registry data, but in general between 2008 and 2022
Sickness absence
Timeframe: depends upon the registry data, but in general between 2008 and 2022