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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Radiomics analysis of placenta on T2WI facilitates prediction of postpartum haemorrhage: A multicentre study
Qingxia Wu, Kuan Yao, Zhenyu Liu, et al.
EBioMedicine (2019) Vol. 50, pp. 355-365
Open Access | Times Cited: 50

Showing 1-25 of 50 citing articles:

A radiomics model for preoperative prediction of brain invasion in meningioma non-invasively based on MRI: A multicentre study
Jing Zhang, Kuan Yao, Panpan Liu, et al.
EBioMedicine (2020) Vol. 58, pp. 102933-102933
Open Access | Times Cited: 89
Predicting risk of postpartum haemorrhage: a systematic review
Colm Neary, Salma Naheed, David J. McLernon, et al.
BJOG An International Journal of Obstetrics & Gynaecology (2020) Vol. 128, Iss. 1, pp. 46-53
Open Access | Times Cited: 87
Predicting EGFR mutation status in lung adenocarcinoma: development and validation of a computed tomography-based radiomics signature.
Guojin Zhang, Yuntai Cao, Jing Zhang, et al.
(2021) Vol. 11, Iss. 2, pp. 546-560
Closed Access | Times Cited: 33
MRI–radiomics–clinical–based nomogram for prenatal prediction of the placenta accreta spectrum disorders
Lulu Peng, Xiang Zhang, Jue Liu, et al.
European Radiology (2022) Vol. 32, Iss. 11, pp. 7532-7543
Closed Access | Times Cited: 22
Segmentation methods applied to MRI-derived radiomic analysis for the prediction of placenta accreta spectrum in patients with placenta previa
Francesco Verde, Arnaldo Stanzione, Renato Cuocolo, et al.
Abdominal Radiology (2023) Vol. 48, Iss. 10, pp. 3207-3215
Closed Access | Times Cited: 12
Normalization Strategies in Multi-Center Radiomics Abdominal MRI: Systematic Review and Meta-Analyses
Jovana Panić, Arianna Defeudis, Gabriella Balestra, et al.
IEEE Open Journal of Engineering in Medicine and Biology (2023) Vol. 4, pp. 67-76
Open Access | Times Cited: 11
Using Multi-phase CT Radiomics Features to Predict EGFR Mutation Status in Lung Adenocarcinoma Patients
Guojin Zhang, Qiong Man, Lan Shang, et al.
Academic Radiology (2024) Vol. 31, Iss. 6, pp. 2591-2600
Closed Access | Times Cited: 4
Association between deep learning radiomics based on placental MRI and preeclampsia with fetal growth restriction: A multicenter study
Weizeng Zheng, Ying Jiang, Zekun Jiang, et al.
European Journal of Radiology (2025) Vol. 184, pp. 111985-111985
Open Access
Perspective in diagnostic accuracy of prenatal ultrasound and MRI for placenta accreta
Qiumin Yang, Chu Zhang, Yunyun Zhang, et al.
The Journal of Maternal-Fetal & Neonatal Medicine (2025) Vol. 38, Iss. 1
Open Access
Predicting placenta accreta spectrum and high postpartum hemorrhage risk using radiomics from T2-weighted MRI
J. H. Zou, Wei Wei, Yanhua Xiao, et al.
BMC Pregnancy and Childbirth (2025) Vol. 25, Iss. 1
Open Access
A machine learning–based framework for predicting postpartum chronic pain: a retrospective study
Fan Liu, Ting Li, Dongxu Zhou, et al.
BMC Medical Informatics and Decision Making (2025) Vol. 25, Iss. 1
Open Access
Predicting postpartum haemorrhage: A systematic review of prognostic models
B. Carr, Maryam Jahangirifar, Ann E. Nicholson, et al.
Australian and New Zealand Journal of Obstetrics and Gynaecology (2022) Vol. 62, Iss. 6, pp. 813-825
Open Access | Times Cited: 17
Prediction of placenta accreta spectrum by combining deep learning and radiomics using T2WI: a multicenter study
Zhengjie Ye, Rongrong Xuan, Menglin Ouyang, et al.
Abdominal Radiology (2022) Vol. 47, Iss. 12, pp. 4205-4218
Closed Access | Times Cited: 16
Radiomics-based prediction of FIGO grade for placenta accreta spectrum
Helena C. Bartels, Jim O’Doherty, Eric Wolsztynski, et al.
European Radiology Experimental (2023) Vol. 7, Iss. 1
Open Access | Times Cited: 10
Placenta Accreta Spectrum Disorders and Radiomics: Systematic review and quality appraisal
Arnaldo Stanzione, Francesco Verde, Renato Cuocolo, et al.
European Journal of Radiology (2022) Vol. 155, pp. 110497-110497
Closed Access | Times Cited: 14
Prediction of placenta accreta spectrum with nomogram combining radiomic and clinical factors: A novel developed and validated integrative model
Yumin Hu, Weiyue Chen, Chunli Kong, et al.
International Journal of Gynecology & Obstetrics (2023) Vol. 162, Iss. 2, pp. 639-650
Closed Access | Times Cited: 8
Predicting the risk of fetal growth restriction by radiomics analysis of the placenta on T2WI: A retrospective case-control study
Fuzhen Song, Ruikun Li, Jing Lin, et al.
Placenta (2023) Vol. 134, pp. 15-22
Closed Access | Times Cited: 8
A novel oppositional binary crow search algorithm with optimal machine learning based postpartum hemorrhage prediction model
Sujatha Krishnamoorthy, Yihang Liu, Kun Liu
BMC Pregnancy and Childbirth (2022) Vol. 22, Iss. 1
Open Access | Times Cited: 13
Prenatal Diagnosis of Placenta Accreta Spectrum Disorders: Deep Learning Radiomics of Pelvic MRI
Lulu Peng, Zehong Yang, Jue Liu, et al.
Journal of Magnetic Resonance Imaging (2023) Vol. 59, Iss. 2, pp. 496-509
Closed Access | Times Cited: 7
From Medical Imaging to Radiomics: Role of Data Science for Advancing Precision Health
Enrico Capobianco, Marco Dominietto
Journal of Personalized Medicine (2020) Vol. 10, Iss. 1, pp. 15-15
Open Access | Times Cited: 20
Predicting risk of postpartum haemorrhage during the intrapartum period in a general obstetric population
Gillian M. Maher, Joye McKernan, Laura O'Byrne, et al.
European Journal of Obstetrics & Gynecology and Reproductive Biology (2022) Vol. 276, pp. 168-173
Open Access | Times Cited: 11
A Deep Learning Pipeline Using Prior Knowledge for Automatic Evaluation of Placenta Accreta Spectrum Disorders With MRI
Haijie Wang, Yida Wang, He Zhang, et al.
Journal of Magnetic Resonance Imaging (2023) Vol. 59, Iss. 2, pp. 483-493
Closed Access | Times Cited: 6
A Magnetic Resonance Imaging-Based Radiomic Model for the Noninvasive Preoperative Differentiation Between Transitional and Atypical Meningiomas
Jing Zhang, Guojin Zhang, Yuntai Cao, et al.
Frontiers in Oncology (2022) Vol. 12
Open Access | Times Cited: 9
MRI-Based Radiomics Analysis for Intraoperative Risk Assessment in Gravid Patients at High Risk with Placenta Accreta Spectrum
Caiting Chu, Ming Liu, Yuzhen Zhang, et al.
Diagnostics (2022) Vol. 12, Iss. 2, pp. 485-485
Open Access | Times Cited: 9
MRI-based radiomics nomogram in patients with high-risk placenta accreta spectrum: can it aid in the prenatal diagnosis of intraoperative blood loss?
Yang Zhang, Meidong Hu, Xuehua Wen, et al.
Abdominal Radiology (2023)
Closed Access | Times Cited: 5
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