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10-05-2024 | Retraction Note

Retraction Note: Prediction of patient’s neurological recovery from cervical spinal cord injury through XGBoost learning approach

Authors: P. Kalyani, Y. Manasa, Sk Hasane Ahammad, M. Suman, Twana Mohammed Kak Anwer, Md. Amzad Hossain, Ahmed Nabih Zaki Rashed

Published in: European Spine Journal

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Excerpt

Retraction Note to: European Spine Journal (2023) 32:2140–2148 https://doi.org/10.1007/s00586-023-07712-6
Literature
1.
go back to reference Inoue T, Ichikawa D, Ueno T, Cheong M, Inoue T, Whetstone WD, Endo T, Nizuma K, Tominaga T (2020) XGBoost, a machine learning method, predicts neurological recovery in patients with cervical spinal cord injury. Neurotrauma Rep 1(1):8–16CrossRefPubMedPubMedCentral Inoue T, Ichikawa D, Ueno T, Cheong M, Inoue T, Whetstone WD, Endo T, Nizuma K, Tominaga T (2020) XGBoost, a machine learning method, predicts neurological recovery in patients with cervical spinal cord injury. Neurotrauma Rep 1(1):8–16CrossRefPubMedPubMedCentral
Metadata
Title
Retraction Note: Prediction of patient’s neurological recovery from cervical spinal cord injury through XGBoost learning approach
Authors
P. Kalyani
Y. Manasa
Sk Hasane Ahammad
M. Suman
Twana Mohammed Kak Anwer
Md. Amzad Hossain
Ahmed Nabih Zaki Rashed
Publication date
10-05-2024
Publisher
Springer Berlin Heidelberg
Published in
European Spine Journal
Print ISSN: 0940-6719
Electronic ISSN: 1432-0932
DOI
https://doi.org/10.1007/s00586-024-08294-7