Prediction of clinical outcomes in women with placenta accreta spectrum using machine learning models: an international multicenter study
Journal
The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians
Journal Volume
35
Journal Issue
25
Pages
6644
Date Issued
2022
Author(s)
Shazly, Sherif A
Hortu, Ismet
Melekoglu, Rauf
Fan, Shangrong
Ahmed, Farhat Ul Ain
Karaman, Erbil
Fatkullin, Ildar
Pinto, Pedro V
Irianti, Setyorini
Tochie, Joel Noutakdie
Abdelbadie, Amr S
Ergenoglu, Ahmet M
Yeniel, Ahmet O
Sagol, Sermet
Itil, Ismail M
Huang, Kuan-Ying
Yilmaz, Ercan
Liang, Yiheng
Aziz, Hijab
Akhter, Tayyiba
Ambreen, Afshan
Ateş, Çağrı
Karaman, Yasemin
Khasanov, Albir
Larisa, Fatkullina
Akhmadeev, Nariman
Vatanina, Adelina
Machado, Ana Paula
Montenegro, Nuno
Effendi, Jusuf S
Suardi, Dodi
Pramatirta, Ahmad Y
Aziz, Muhamad A
Siddiq, Amilia
Ofakem, Ingrid
Dohbit, Julius Sama
Fahmy, Mohamed S
Anan, Mohamed A
Abstract
Placenta accreta spectrum is a major obstetric disorder that is associated with significant morbidity and mortality. The objective of this study is to establish a prediction model of clinical outcomes in these women.
Subjects
Obstetric hemorrhage; cesarean hysterectomy; machine learning; morbidly adherent placenta; placenta accreta spectrum; placenta praevia
Type
journal article