Response to Folweiler KA et al., Unsupervised Machine Learning Reveals Novel Traumatic Brain Injury Patient Phenotypes With Distinct Acute Injury Profiles and Long-Term Outcomes (DOI: 10.1089/neu.2019.6705)
J Neurotrauma
.
2024 Jan;41(1-2):292-293.
doi: 10.1089/neu.2023.0396.
Epub 2023 Oct 18.
Authors
Ching-Ying Wang
1
2
,
Jau-Ching Wu
1
2
,
Yi-Hsuan Kuo
1
2
3
Affiliations
1
Department of Neurosurgery, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan.
2
School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.
3
Institute of Biomedical Informatics, National Yang Ming Chiao Tung University, Taipei, Taiwan.
PMID:
37756375
DOI:
10.1089/neu.2023.0396
No abstract available
Publication types
Letter
Comment
MeSH terms
Brain Injuries, Traumatic*
Humans
Phenotype
Unsupervised Machine Learning*