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