# Prediction of clinical outcomes in women with placenta accreta spectrum using machine learning models: an international multicenter study

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/prediction-of-clinical-outcomes-in-women-with-placenta-accreta-spectrum-using/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Sherif A. Shazly,İsmet Hortu,Jin‐Chung Shih,Rauf Melekoğlu,Shang­rong Fan,Farhat ul Ain Ahmed,Erbil Karaman,И. Ф. Фаткуллин,Pedro Viana Pinto,Setyorini Irianti,Joël Noutakdie Tochie,Amr S. Abdelbadie,Ahmet Mete Ergenoğlu,Ahmet Özgür Yeniel,Sermet Sağol,Ismail M. Itil,Jessica Kang,Kuan‐Ying Huang,Ercan Yılmaz,Yiheng Liang,Hijab Aziz,Tayyiba Akhter,Afshan Ambreen,Çağrı Ateş,Yasemin Karaman,А. А. Хасанов,Fatkullina Larisa,Nariman R Akhmadeev,Adelina Vatanina,Ana Paula Machado,Nuno Montenegro,Jusuf Sulaeman Effendi,Dodi Suardi,Ahmad Y. Pramatirta,Muhamad A. Aziz,Amilia Siddiq,Ingrid Ofakem,Julius Sama Dohbit,Mohamed S. Fahmy,Mohamed A. Anan,and Middle East Obstetrics and Gynecology Graduate Education (MOGGE) foundation – Artificial intelligence (AI) unit |
| Citations | 27 |
| DOI | 10.1080/14767058.2021.1918670 |
| Fields | Medicine |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W3179112989 |
| PMID | 34233555 |
| Type | article |
| Year | 2021 |

## Paper authors

- [Julius Sama Dohbit](https://scholariq.org/researchers/julius-sama-dohbit/)

## Paper journal

- [The Journal of Maternal-Fetal & Neonatal Medicine](https://scholariq.org/journals/the-journal-of-maternal-fetal-and-neonatal-medicine/)

## Paper primary topic

- [Maternal and fetal healthcare](https://scholariq.org/topics/maternal-and-fetal-healthcare/)

## Paper topics

- [Maternal and fetal healthcare](https://scholariq.org/topics/maternal-and-fetal-healthcare/)
- [Pregnancy and preeclampsia studies](https://scholariq.org/topics/pregnancy-and-preeclampsia-studies/)
- [Blood transfusion and management](https://scholariq.org/topics/blood-transfusion-and-management/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.