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2016

A Prediction Model for Functional Outcomes in Spinal Cord Disorder Patients Using Gaussian Process Regression

3 years 9 months ago
A Prediction Model for Functional Outcomes in Spinal Cord Disorder Patients Using Gaussian Process Regression
Abstract—Predicting the functional outcomes of spinal cord disorder patients after medical treatments, such as a surgical operation, has always been of great interest. Accurate posttreatment prediction is especially beneficial for clinicians, patients, care givers, and therapists. This paper introduces a prediction method for postoperative functional outcomes by a novel use of Gaussian process regression. The proposed method specifically considers the restricted value range of the target variables by modeling the Gaussian process based on a truncated Normal distribution, which significantly improves the prediction results. The prediction has been made in assistance with target tracking examinations using a highly portable and inexpensive handgrip device, which greatly contributes to the prediction performance. The proposed method has been validated through a dataset collected from a clinical cohort pilot involving 15 patients with cervical spinal cord disorder. The results show th...
Sunghoon Ivan Lee, Bobak Mortazavi, Haydn A. Hoffm
Added 11 Apr 2016
Updated 11 Apr 2016
Type Journal
Year 2016
Where TITB
Authors Sunghoon Ivan Lee, Bobak Mortazavi, Haydn A. Hoffman, Derek S. Lu, Charles Li, Brian H. Paak, Jordan H. Garst, Mehrdad Razaghy, Marie Espinal, Eunjeong Park, Daniel C. Lu, Majid Sarrafzadeh
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