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Machine learning XGBoost classification of postoperative delirium by intraoperative EEG metrics

Publication ,  Conference
Reese, M; Roberts, K; Woldorff, MG; Cooter, M; Acker, L; Wu, S; Whitson, HE; Berger, M
Published in: ANESTHESIA AND ANALGESIA
2022

Duke Scholars

Published In

ANESTHESIA AND ANALGESIA

ISSN

0003-2999

Publication Date

2022

Volume

134

Start / End Page

609 / 611

Related Subject Headings

  • Anesthesiology
  • 3202 Clinical sciences
  • 1109 Neurosciences
  • 1103 Clinical Sciences
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Reese, M., Roberts, K., Woldorff, M. G., Cooter, M., Acker, L., Wu, S., … Berger, M. (2022). Machine learning XGBoost classification of postoperative delirium by intraoperative EEG metrics. In ANESTHESIA AND ANALGESIA (Vol. 134, pp. 609–611).
Reese, Melody, Ken Roberts, Marty G. Woldorff, Mary Cooter, Leah Acker, Sophie Wu, Heather E. Whitson, and Miles Berger. “Machine learning XGBoost classification of postoperative delirium by intraoperative EEG metrics.” In ANESTHESIA AND ANALGESIA, 134:609–11, 2022.
Reese M, Roberts K, Woldorff MG, Cooter M, Acker L, Wu S, et al. Machine learning XGBoost classification of postoperative delirium by intraoperative EEG metrics. In: ANESTHESIA AND ANALGESIA. 2022. p. 609–11.
Reese, Melody, et al. “Machine learning XGBoost classification of postoperative delirium by intraoperative EEG metrics.” ANESTHESIA AND ANALGESIA, vol. 134, 2022, pp. 609–11.
Reese M, Roberts K, Woldorff MG, Cooter M, Acker L, Wu S, Whitson HE, Berger M. Machine learning XGBoost classification of postoperative delirium by intraoperative EEG metrics. ANESTHESIA AND ANALGESIA. 2022. p. 609–611.

Published In

ANESTHESIA AND ANALGESIA

ISSN

0003-2999

Publication Date

2022

Volume

134

Start / End Page

609 / 611

Related Subject Headings

  • Anesthesiology
  • 3202 Clinical sciences
  • 1109 Neurosciences
  • 1103 Clinical Sciences