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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:

Multi-centre deep learning for placenta segmentation in obstetric ultrasound with multi-observer and cross-country generalization
Lisbeth Anita Andreasen, Aasa Feragen, Anders Nymark Christensen, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 11

Showing 11 citing articles:

Evolving the Era of 5D Ultrasound? A Systematic Literature Review on the Applications for Artificial Intelligence Ultrasound Imaging in Obstetrics and Gynecology
Elena Jost, Philipp Kosian, J Jiménez Cruz, et al.
Journal of Clinical Medicine (2023) Vol. 12, Iss. 21, pp. 6833-6833
Open Access | Times Cited: 23
Artificial intelligence, radiomics and fetal ultrasound: review of literature and future perspectives
Amine Bouachba, Joana De Jesus Neves, Éric Royer, et al.
Ultrasound in Obstetrics and Gynecology (2025)
Closed Access
Bridging Gaps in Artificial Intelligence Adoption for Maternal-Fetal and Obstetric Care: Unveiling Transformative Capabilities and Challenges
Kalyan Tadepalli, Abhijit Das, Tanushree Meena, et al.
Computer Methods and Programs in Biomedicine (2025) Vol. 263, pp. 108682-108682
Closed Access
Ensemble learning for fetal ultrasound and maternal–fetal data to predict mode of delivery after labor induction
Iolanda Ferreira, Joana Simões, Beatriz Magalhães Pereira, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 3
Analytical study of the encoder-decoder models for ultrasound image segmentation
Somya Srivastava, Ankit Vidyarthi, Shikha Jain
Service Oriented Computing and Applications (2023) Vol. 18, Iss. 1, pp. 81-100
Closed Access | Times Cited: 7
Validity evidence supporting clinical skills assessment by artificial intelligence compared with trained clinician raters
Vilma Johnsson, Morten Søndergaard, Kulamakan Kulasegaram, et al.
Medical Education (2023) Vol. 58, Iss. 1, pp. 105-117
Open Access | Times Cited: 7
Early Prediction of Placenta Accreta Spectrum by Different Modalities: An Evidenced-based Analysis
Heba Rady Elbasuiny, Ayman Shehata Dawood, Mohamed Atia Raslan
Clinical and Experimental Obstetrics & Gynecology (2024) Vol. 51, Iss. 1, pp. 27-27
Open Access | Times Cited: 1
Navigating Uncertainty in Medical Image Segmentation
Kilian Zepf, Jes Frellsen, Aasa Feragen
(2024), pp. 1-5
Closed Access
Automated Deep Learning Detection Algorithms for Fetal Orientation and Placenta Previa
Joshua Eisenstat
(2024)
Open Access
Automated Deep Learning Detection Algorithms for Fetal Orientation and Placenta Previa
Joshua Eisenstat
(2024)
Open Access
Analysis of the Value of Multimodal Ultrasound Combined with AI in Evaluating Placental Function in Gestational Diabetes Mellitus
妍春 张
Advances in Clinical Medicine (2024) Vol. 14, Iss. 10, pp. 1006-1013
Closed Access
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