Optimal machine learning methods for radiomic prediction models: Clinical application for preoperative T 2 *‐weighted images of cervical spondylotic myelopathy-Reference-Cited by-同舟云学术

Optimal machine learning methods for radiomic prediction models: Clinical application for preoperative T 2 *‐weighted images of cervical spondylotic myelopathy

Published:2021-11-13 Issue:4 Volume:4 Page:
ISSN:2572-1143
Container-title:JOR SPINE
language:en
Short-container-title:JOR Spine

Author:

Zhang Meng‐Ze¹^ORCID,Ou‐Yang Han‐Qiang²³⁴,Jiang Liang²³⁴,Wang Chun‐Jie¹,Liu Jian‐Fang¹,Jin Dan¹,Ni Ming¹,Liu Xiao‐Guang²³⁴,Lang Ning¹,Yuan Hui‐Shu¹

Affiliation:

1. Department of Radiology Peking University Third Hospital Beijing China

2. Department of Orthopedics Peking University Third Hospital Beijing China

3. Beijing Key Laboratory of Spinal Disease Research Beijing China

4. Engineering Research Center of Bone and Joint Precision Medicine, Ministry of Education Beijing China

Funder

Natural Science Foundation of Beijing Municipality

National Natural Science Foundation of China

Publisher

Wiley

Subject

Orthopedics and Sports Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/jsp2.1178

Reference42 articles.

1. Cervical Spondylotic Myelopathy

2. Degenerative Cervical Myelopathy

3. Cervical Spondylotic Myelopathy

4. Current Diagnosis and Management of Cervical Spondylotic Myelopathy

5. Does Magnetic Resonance Imaging Improve the Predictive Performance of a Validated Clinical Prediction Rule Developed to Evaluate Surgical Outcome in Patients With Degenerative Cervical Myelopathy?

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