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256: Machine learning-based prediction models for postpartum hemorrhage

Publication ,  Conference
Venkatesh, KK; Strauss, R; Grotegut, C; Heine, P; Stamilio, DM; Menard, K; Jelovsek, E
Published in: American Journal of Obstetrics and Gynecology
January 2020

Duke Scholars

Published In

American Journal of Obstetrics and Gynecology

DOI

ISSN

0002-9378

Publication Date

January 2020

Volume

222

Issue

1

Start / End Page

S175 / S176

Publisher

Elsevier BV

Related Subject Headings

  • Obstetrics & Reproductive Medicine
  • 3215 Reproductive medicine
  • 1114 Paediatrics and Reproductive Medicine
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Venkatesh, K. K., Strauss, R., Grotegut, C., Heine, P., Stamilio, D. M., Menard, K., & Jelovsek, E. (2020). 256: Machine learning-based prediction models for postpartum hemorrhage. In American Journal of Obstetrics and Gynecology (Vol. 222, pp. S175–S176). Elsevier BV. https://doi.org/10.1016/j.ajog.2019.11.272
Venkatesh, Kartik K., Robert Strauss, Chad Grotegut, Phillips Heine, David M. Stamilio, Kathryn Menard, and Eric Jelovsek. “256: Machine learning-based prediction models for postpartum hemorrhage.” In American Journal of Obstetrics and Gynecology, 222:S175–76. Elsevier BV, 2020. https://doi.org/10.1016/j.ajog.2019.11.272.
Venkatesh KK, Strauss R, Grotegut C, Heine P, Stamilio DM, Menard K, et al. 256: Machine learning-based prediction models for postpartum hemorrhage. In: American Journal of Obstetrics and Gynecology. Elsevier BV; 2020. p. S175–6.
Venkatesh, Kartik K., et al. “256: Machine learning-based prediction models for postpartum hemorrhage.” American Journal of Obstetrics and Gynecology, vol. 222, no. 1, Elsevier BV, 2020, pp. S175–76. Crossref, doi:10.1016/j.ajog.2019.11.272.
Venkatesh KK, Strauss R, Grotegut C, Heine P, Stamilio DM, Menard K, Jelovsek E. 256: Machine learning-based prediction models for postpartum hemorrhage. American Journal of Obstetrics and Gynecology. Elsevier BV; 2020. p. S175–S176.
Journal cover image

Published In

American Journal of Obstetrics and Gynecology

DOI

ISSN

0002-9378

Publication Date

January 2020

Volume

222

Issue

1

Start / End Page

S175 / S176

Publisher

Elsevier BV

Related Subject Headings

  • Obstetrics & Reproductive Medicine
  • 3215 Reproductive medicine
  • 1114 Paediatrics and Reproductive Medicine