Artificial Intelligence and Machine Learning in Spinal Cord Injury

Spinal cord injury (SCI) is a complex and heterogeneous condition associated with substantial neurologic disability, functional impairment, and socioeconomic burden. Artificial intelligence (AI) and machine learning are increasingly being applied throughout the SCI care continuum to improve diagnosis, imaging analysis, prognostication, phenotyping, and therapeutic decision-making. Unsupervised learning approaches further support data-driven patient phenotyping and personalized rehabilitation strategies. Emerging applications also extend to regenerative medicine, where AI may optimize patient selection, monitor neural repair, and enhance therapeutic integration. Collectively, these advances support a transition toward precision, data-driven, and individualized SCI management.