XGBoost, a Machine Learning Method, Predicts Neurological Recovery in Patients with Cervical Spinal Cord Injury

The accurate prediction of neurological outcomes in patients with cervical spinal cord injury (SCI) is difficult because of heterogeneity in patient characteristics, treatment strategies, and radiographic findings. Although machine learning algorithms may increase the accuracy of outcome predictions...

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Detalles Bibliográficos
Autores principales: Inoue, Tomoo, Ichikawa, Daisuke, Ueno, Taro, Cheong, Maxwell, Inoue, Takashi, Whetstone, William D., Endo, Toshiki, Nizuma, Kuniyasu, Tominaga, Teiji
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Mary Ann Liebert, Inc., publishers 2020
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8240917/
https://www.ncbi.nlm.nih.gov/pubmed/34223526
http://dx.doi.org/10.1089/neur.2020.0009

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8240917/
https://www.ncbi.nlm.nih.gov/pubmed/34223526
http://dx.doi.org/10.1089/neur.2020.0009

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