Quality of birth care and risk factors of length of stay after birth: A machine learning approach

Type of delivery which is an indicator of quality of birth care is a strong predictor of LOS after birth according to the Random Forest model. We demonstrated that machine learning techniques offer precise LOS prediction after birth. Further studies assessing the effect of quality of birth care on predicting LOS at birth would be beneficial.

Authors

Institutions

Publication Details

Journal
Journal of obstetrics and gynaecology research
Published
2024-09-16
DOI
https://doi.org/10.1111/jog.16072
Primary Topic
Global Maternal and Child Health
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Quality of birth care and risk factors of length of stay after birth: A machine learning approach

Songül Çınaroğlu, Büşra Saylan
Journal of obstetrics and gynaecology research
Global Maternal and Child Health
article

Quality of birth care and risk factors of length of stay after birth: A machine learning approach

Songül Çınaroğlu, Büşra Saylan
article en

Abstract

Type of delivery which is an indicator of quality of birth care is a strong predictor of LOS after birth according to the Random Forest model. We demonstrated that machine learning techniques offer precise LOS prediction after birth. Further studies assessing the effect of quality of birth care on predicting LOS at birth would be beneficial.

Journal of obstetrics and gynaecology researchVol. 50(10)
Hacettepe University (TR)
Openalex Percentile: Top 75%
Global Maternal and Child Health
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Quality of birth care and risk factors of length of stay after birth: A machine learning approach — Songül Çınaroğlu, Büşra Saylan · Journal of obstetrics and gynaecology research (2024) | TGRS Research Map | TGRS