Papers of the Week

Chronic spinal pain is the most prevalent chronic disease, with chronic persistent spinal pain lasting longer than one-year reported in 25% to 60% of the patients. Health care expenditures have been escalating and the financial impact on the US economy is growing. Among multiple modalities of treatments available, facet joint interventions and epidural interventions are the most common ones, in addition to surgical interventions and numerous other conservative modalities of treatments. Despite these increasing costs in the diagnosis and management, disability continues to increase. Consequently, algorithmic approaches have been described as providing a disciplined approach to the use of spinal interventional techniques in managing spinal pain. This approach includes evaluative, diagnostic, and therapeutic approaches, which avoids unnecessary care, as well as poorly documented practices.  Recently, techniques involving artificial intelligence and machine learning have been demonstrated to contribute to the improved understanding, diagnosis, and management of both acute and chronic disease in line with well-designed algorithmic approach. The use of artificial intelligence and machine-learning techniques for the diagnosis of spinal pain has not been widely investigated or adopted.