Artificial Neural Network Analysis of Spontaneous Preterm Labor and Birth and Its Major Determinants
10.3346/jkms.2019.34.e128
- Author:
Kwang Sig LEE
1
;
Ki Hoon AHN
Author Information
1. Center for Artificial Intelligence, Korea University College of Medicine, Seoul, Korea.
- Publication Type:Original Article
- Keywords:
Preterm Birth;
Hypertension;
Diabetes Mellitus;
Prior Conization;
Cervical-Length Screening
- MeSH:
Adenomyosis;
Biopsy;
Body Mass Index;
Conization;
Diabetes Mellitus;
Female;
Forests;
Humans;
Hypertension;
Korea;
Logistic Models;
Machine Learning;
Mass Screening;
Myoma;
Obstetric Labor, Premature;
Parity;
Parturition;
Placenta Previa;
Pregnancy;
Premature Birth;
Seoul
- From:Journal of Korean Medical Science
2019;34(16):e128-
- CountryRepublic of Korea
- Language:English
-
Abstract:
BACKGROUND: Little research based on the artificial neural network (ANN) is done on preterm birth (spontaneous preterm labor and birth) and its major determinants. This study uses an ANN for analyzing preterm birth and its major determinants.
