Predicting cesarean delivery with decision tree models

American Journal of Obstetrics and Gynecology

Volumn 183, Issue 5, 2000, Pages 1198-1206

  Sims, Cynthia J ^a,b,c,d   Meyn, Leslie ^a,b,c,d   Caruana, Rich ^a,b,c,d   Rao, R Bharat ^a,b,c,d   Mitchell, Tom ^a,b,c,d   Krohn, Marijane ^a,b,c,d  

^a UNIVERSITY OF PITTSBURGH   (United States)

^b Carnegie Mellon University   (United States)

^c UNIVERSITY OF CALIFORNIA   (United States)

^d SIEMENS CORPORATE RESEARCH   (United States)

Author keywords

Decision trees; Machine learning; Predicting cesarean delivery; Statistical models

Indexed keywords

ADULT; CESAREAN SECTION; CONFERENCE PAPER; CONTROLLED STUDY; DECISION THEORY; DELIVERY; FEMALE; HUMAN; MATERNAL MORBIDITY; MATERNAL MORTALITY; NORMAL HUMAN; NULLIPARA; PARITY; PRIORITY JOURNAL; RISK FACTOR;

EID: 0033666648     PISSN: 00029378     EISSN: None     Source Type: Journal    
DOI: 10.1067/mob.2000.108891     Document Type: Conference Paper

References (14)

1. Rates of cesarean delivery - United States, 1993
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4. Racial/ethnic differences in the likelihood of cesarean delivery, California
5. Race, age, and cesarean delivery in a military population
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7. Maternal age: An independent risk factor for cesarean delivery
8. Development of a cesarean delivery risk score
9. Tree-based risk factor analysis of preterm delivery and small-for-gestational-age birth
10. Tree-based, two-stage risk factor analysis for spontaneous abortion