Development of an unsupervised machine learning algorithm for the prognostication of walking ability in spinal cord injury patients.

Background Context: Traumatic spinal cord injury can have a dramatic effect on a patient's life. The degree of neurologic recovery greatly influences a patient's treatment and expected quality of life. This has resulted in the development of machine learning algorithms (MLA) that use acute demographic and neurologic information to prognosticate recovery.