Utilizing machine learning to predict unplanned cesarean delivery-Reference-Cited by-同舟云学术

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Utilizing machine learning to predict unplanned cesarean delivery

Published:2022-09-18 Issue:1 Volume:161 Page:255-263
ISSN:0020-7292
Container-title:International Journal of Gynecology & Obstetrics
language:en
Short-container-title:Intl J Gynecology & Obste

Author:

Meyer Raanan¹²³^ORCID,Weisz Boaz¹²³,Eilenberg Roni⁴,Tsadok Meytal Avgil⁴,Uziel Moshe⁴,Sivan Eyal¹²,Mazaki‐Tovi Shali¹²³,Tsur Abraham¹²⁵

Affiliation:

1. Department of Obstetrics and Gynecology The Chaim Sheba Medical Center Tel Hashomer Israel

2. School of Medicine Tel Aviv University Tel Aviv‐Yafo Israel

3. The Dr. Pinchas Bornstein Talpiot Medical Leadership Program Sheba Medical Center, Tel Hashomer Ramat‐Gan Israel

4. Timna, Big Data Department Israel Ministry of Health Jerusalem Israel

5. The Gertner Institute for Epidemiology and Health Policy Tel HaShomer Israel

Publisher

Wiley

Subject

Obstetrics and Gynecology,General Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/ijgo.14433

Reference23 articles.

1. New labor management guidelines and changes in cesarean delivery patterns

2. Prediction of cesarean delivery in the term nulliparous woman: results from the prospective, multicenter Genesis study

3. Intervention thresholds and cesarean section rates: A time-trends analysis

4. A validated calculator to estimate risk of cesarean after an induction of labor with an unfavorable cervix

5. Comparison of Maternal and Infant Outcomes From Primary Cesarean Delivery During the Second Compared With First Stage of Labor

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