https://scholars.lib.ntu.edu.tw/handle/123456789/583797
Title: | Prediction of clinical outcomes in women with placenta accreta spectrum using machine learning models: an international multicenter study | Authors: | Shazly, Sherif A Hortu, Ismet JIN-CHUNG SHIH 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 Jessica KANG 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 |
Keywords: | Obstetric hemorrhage; cesarean hysterectomy; machine learning; morbidly adherent placenta; placenta accreta spectrum; placenta praevia | Issue Date: | 2022 | Journal Volume: | 35 | Journal Issue: | 25 | Start page/Pages: | 6644 | Source: | 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 | 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. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/583797 | ISSN: | 14767058 | DOI: | 10.1080/14767058.2021.1918670 |
Appears in Collections: | 醫學系 |
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