Machine Learning Approach in Predicting Clinically Significant Improvements After Surgery in Patients with Cervical Ossification of the Posterior Longitudinal Ligament-Reference-Cited by-同舟云学术

Machine Learning Approach in Predicting Clinically Significant Improvements After Surgery in Patients with Cervical Ossification of the Posterior Longitudinal Ligament

Published:2021-05-21 Issue:24 Volume:46 Page:1683-1689
ISSN:0362-2436
Container-title:Spine
language:en
Short-container-title:

Author:

Maki Satoshi,Furuya Takeo,Yoshii Toshitaka,Egawa Satoru,Sakai Kenichiro,Kusano Kazuo,Nakagawa Yukihiro,Hirai Takashi,Wada Kanichiro,Katsumi Keiichi,Fujii Kengo,Kimura Atsushi,Nagoshi Narihito,Kanchiku Tsukasa,Nagamoto Yukitaka,Oshima Yasushi,Ando Kei,Takahata Masahiko,Mori Kanji,Nakajima Hideaki,Murata Kazuma,Matsunaga Shunji,Kaito Takashi,Yamada Kei,Kobayashi Sho,Kato Satoshi,Ohba Tetsuro,Inami Satoshi,Fujibayashi Shunsuke,Katoh Hiroyuki,Kanno Haruo,Imagama Shiro,Koda Masao,Kawaguchi Yoshiharu,Takeshita Katsushi,Matsumoto Morio,Ohtori Seiji,Yamazaki Masashi,Okawa Atsushi

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Neurology (clinical),Orthopedics and Sports Medicine

Reference20 articles.

1. Surgical strategy for cervical myelopathy due to ossification of the posterior longitudinal ligament: Part 1: clinical results and limitations of laminoplasty;Iwasaki;Spine (Phila Pa 1976),2007

2. XGBoost, a machine learning method, predicts neurological recovery in patients with cervical spinal cord injury;Inoue;Neurotrauma Rep,2020

3. AOSpine North America and International Clinical Trial Research Network. A clinical prediction model to assess surgical outcome in patients with cervical spondylotic myelopathy: Internal and external validations using the prospective multicenter AOSpine North American and international datasets of 743 patients;Tetreault;Spine J,2015

4. A clinical prediction model to determine outcomes in patients with cervical spondylotic myelopathy undergoing surgical treatment: Data from the prospective, multi-center AOSpine North America study;Tetreault;J Bone Joint Surg Am,2013

5. Potential risk factors for poor outcome after anterior surgery for patients with cervical ossification of the posterior longitudinal ligament;Li;Ther Clin Risk Manag,2018

Cited by 12 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Machine-learning-based prediction by stacking ensemble strategy for surgical outcomes in patients with degenerative cervical myelopathy;Journal of Orthopaedic Surgery and Research;2024-09-04

2. Developing predictive models for surgical outcomes in patients with degenerative cervical myelopathy: a comparison of statistical and machine learning approaches;The Spine Journal;2024-01

3. Models to predict the surgical outcome of mini-ECIRS (endoscopic combined intrarenal surgery) for renal and/or ureteral stones;Scientific Reports;2023-12-21

4. Predicting conversion of ambulatory ACDF patients to inpatient: a machine learning approach;The Spine Journal;2023-11

5. To infer the probability of cervical ossification of the posterior longitudinal ligament and explore its impact on cervical surgery;Scientific Reports;2023-06-17