A Prediction Model for Functional Outcomes in Spinal Cord Disorder Patients Using Gaussian Process Regression
A Prediction Model for Functional Outcomes in Spinal Cord Disorder Patients Using Gaussian Process Regression
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DOI：
10.1109/jbhi.2014.2372777
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发表时间：
2016-01-01
影响因子：
7.7
通讯作者：
Sarrafzadeh, Majid
中科院分区：
文献类型：
--
作者：
Lee, Sunghoon Ivan;Mortazavi, Bobak;Sarrafzadeh, Majid
预测脊髓疾病患者在医学治疗（例如外科手术）后的功能结果一直备受关注。准确的治疗后预测对临床医生、患者、护理人员和治疗师特别有益。本文介绍了一种新的使用高斯过程回归预测术后功能结果的方法。该方法考虑了目标变量取值范围的限制，采用截尾正态分布对高斯过程进行建模，显著提高了预测结果。预测已经作出了援助与目标跟踪检查使用一个高度便携式和廉价的手柄设备，这大大有助于预测性能。所提出的方法已通过从涉及15名颈脊髓疾病患者的临床队列试点中收集的数据集进行了验证。结果表明，所提出的方法可以准确地预测术后功能的结果，奥斯韦斯特里残疾指数和目标跟踪评分，根据患者的术前信息的平均绝对误差为0.079和0.014（满分1.0），分别。
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 that the proposed method can accurately predict postoperative functional outcomes, Oswestry disability index and target tracking scores, based on the patient's preoperative information with a mean absolute error of 0.079 and 0.014 (out of 1.0), respectively.