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)
Restricted accessLetterFirst published online January, 2024
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)
FolweilerKA, SandsmarkDK, Diaz-ArrastiaR, et al.Unsupervised machine learning reveals novel traumatic brain injury patient phenotypes with distinct acute injury profiles and long-term outcomes. J Neurotrauma, 2020; 37(12):1431–1444; doi:10.1089/neu.2019.6705
2.
ZafonteRD, BagiellaE, AnselBM, et al.Effect of citicoline on functional and cognitive status among patients with traumatic brain injury: Citicoline Brain Injury Treatment Trial (COBRIT). JAMA, 2012; 308(19):1993–2000; doi:10.1001/jama.2012.13256
3.
DorgalalehA, FavaloroEJ, BahrainiM, et al.Standardization of Prothrombin Time/International Normalized Ratio (PT/INR). Int J Lab Hematol, 2021; 43(1):21–28; doi:10.1111/ijlh.13349
