Prediction of patient's neurological recovery from cervical spinal cord injury through XGBoost learning approach.

Kalyani P, Manasa Y, Ahammad SH, Suman M, Anwer TMK, Hossain MA, Rashed ANZ.

DOI: 10.1007/s00586-023-07712-6
Published: 2023-04-15
Container: Eur Spine J
Publisher: Not recorded
Open access: no

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Cite this work

BibTeX

@article{allodium:10.1007/s00586-023-07712-6,
  title = {Prediction of patient's neurological recovery from cervical spinal cord injury through XGBoost learning approach.},
  author = {Kalyani P and  Manasa Y and  Ahammad SH and  Suman M and  Anwer TMK and  Hossain MA and  Rashed ANZ.},
  year = {2023},
  journal = {Eur Spine J},
  doi = {10.1007/s00586-023-07712-6},
  url = {https://doi.org/10.1007/s00586-023-07712-6}
}

RIS

TY  - JOUR
TI  - Prediction of patient's neurological recovery from cervical spinal cord injury through XGBoost learning approach.
AU  - Kalyani P
AU  -  Manasa Y
AU  -  Ahammad SH
AU  -  Suman M
AU  -  Anwer TMK
AU  -  Hossain MA
AU  -  Rashed ANZ.
PY  - 2023
JO  - Eur Spine J
DO  - 10.1007/s00586-023-07712-6
UR  - https://doi.org/10.1007/s00586-023-07712-6
ER  -

APA

P, K., Y, M., SH, A., M, S., TMK, A., MA, H., & ANZ., R. (2023). Prediction of patient's neurological recovery from cervical spinal cord injury through XGBoost learning approach.. Eur Spine J. https://doi.org/10.1007/s00586-023-07712-6

Source records

europe-pmc · retrieved 2026-09-25T20:23:40.802Z