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

Traumatic spinal cord injury can have a dramatic effect on a patient's life. The degree of neurological 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 neurological information to prognosticate recovery. The van Middendorp et al. (2011) (vM) logistic regression (LR) model has been established as a reference model for the prediction of walking recovery following spinal cord injury as it has been validated within many different countries.

Source: The Spine Journal - September 12, 2019 Category: Orthopaedics Authors: Zachary DeVries, Mohamad Hoda, Carly Rivers, Audrey Maher, Eugene Wai, Dita Moravek, Alexandra Stratton, Stephen Kingwell, Nader Fallah, J érôme Paquet, Philippe Phan, The RHSCIR Network Tags: Clinical Study Source Type: research