Robotics & Machine Learning Daily News2024,Issue(Feb.9) :6-7.

Guangxi Medical University First Affiliated Hospital Reports Findings in Radiculopathy (Age and flexors as risk factors for cervical radiculopathy: A new machine learning method)

Robotics & Machine Learning Daily News2024,Issue(Feb.9) :6-7.

Guangxi Medical University First Affiliated Hospital Reports Findings in Radiculopathy (Age and flexors as risk factors for cervical radiculopathy: A new machine learning method)

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Abstract

New research on Nervous System Diseases and Conditions Radiculopathy is the subject of a report. According to news reporting from Nanning, People’s Republic of China, by NewsRx journalists, research stated, “This study aimed to investigate the risk factors for cervical radiculopathy (CR) along with identifying the relationships between age, cervical flexors, and CR. This was a retrospective cohort study, including 60 patients with CR enrolled between December 2018 and June 2020.” The news correspondents obtained a quote from the research from Guangxi Medical University First Affiliated Hospital, “In this study, we measured C2 to C7 Cobb angle, disc degeneration, endplate degeneration, and morphology of paraspinal muscles and evaluated the value of predictive methods using receiver operating characteristic curves. Next, we established a diagnostic model for CR using Fisher discriminant model and compared different models by calculating the kappa value. Age and cervical flexor factors were used to construct clinical predictive models, which were further evaluated by C-index, receiver operating characteristic curve, calibration curve, and decision curve analysis. Multivariate analysis showed that age and cervical flexors were potential risk factors for CR, while the diagnostic model indicated that both exerted the best diagnostic effect. The obtained diagnostic equation was as follows: y1 = 0.33 x 1 + 10.302 x 2-24.139; y2 = 0.259 x 1 + 13.605 x 2-32.579. Both the C-index and AUC in the training set reached 0.939. Moreover, the C-index and AUC values in the external validation set reached 0.961. We developed 2 models for predicting CR and also confirmed their validity. Age and cervical flexors were considered potential risk factors for CR.”

Key words

Nanning/People’s Republic of China/Asia/Cervical Radiculopathy/Cyborgs/Emerging Technologies/Health and Medicine/Machine Learning/Nervous System Diseases and Conditions/Neuromuscular Diseases and Conditions/Peripheral Nervous System Diseases and Conditions/Radiculopathy/Risk and Prevention

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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