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:

Detecting cardiomyopathies in pregnancy and the postpartum period with an electrocardiogram-based deep learning model
Demilade Adedinsewo, Patrick W. Johnson, Erika J. Douglass, et al.
European Heart Journal - Digital Health (2021) Vol. 2, Iss. 4, pp. 586-596
Open Access | Times Cited: 34

Showing 26-50 of 34 citing articles:

Using Technology to Deliver Cardiovascular Care in African Countries
Zainab Mahmoud, Muhammad Sanusi, Cecilia Nartey, et al.
Current Cardiology Reports (2023) Vol. 25, Iss. 12, pp. 1823-1830
Closed Access | Times Cited: 2

Automated electrocardiogram signal quality assessment based on Fourier analysis and template matching
Kartikeya M. Menon, Subrat Das, Mark Shervey, et al.
Journal of Clinical Monitoring and Computing (2022) Vol. 37, Iss. 3, pp. 829-837
Open Access | Times Cited: 3

Artificial Intelligence Solutions for Cardiovascular Disease Detection and Management in Women: Promise and Perils
Wendy Tatiana Garzon-Siatoya, Andrea Carolina Morales-Lara, Demilade Adedinsewo
Cardiovascular Innovations and Applications (2023) Vol. 8, Iss. 1
Open Access | Times Cited: 1

Novel adaptation of the KCC-questionnaire for cardiomyopathy screening in a racially diverse obstetric population
Demilade Adedinsewo, Andrea Carolina Morales-Lara, Heather Hardway, et al.
npj Women s Health (2024) Vol. 2, Iss. 1
Open Access

A bibliometric review of peripartum cardiomyopathy compared to other cardiomyopathies using artificial intelligence and machine learning
Mark Grosser, Hua Lin, Mengjia Wu, et al.
Biophysical Reviews (2022) Vol. 14, Iss. 1, pp. 381-401
Open Access | Times Cited: 2

Can artificial intelligence improve cardiovascular disease screening in pregnancy? The digital future and cardio-obstetrics
Andrea Carolina Morales-Lara, Demilade Adedinsewo
International Journal of Cardiology (2022) Vol. 354, pp. 48-49
Closed Access | Times Cited: 1

State-of-the-art Deep Learning Methods on Electrocardiogram Data: A Systematic Review (Preprint)
Georgios Petmezas, Leandros Stefanopoulos, Vassiis Kilintzis, et al.
(2022)
Closed Access | Times Cited: 1

Artificial intelligence and cardiovascular disease in women
Beatriz A. Fernandez-Campos, Demilade Adedinsewo, Wendy Tsang, et al.
Elsevier eBooks (2023), pp. 285-295
Closed Access

Automated Electrocardiogram Signal Quality Assessment Based on Fourier Analysis and Template Matching
Kartikeya M. Menon, Subrat Das, Mark Shervey, et al.
Research Square (Research Square) (2022)
Open Access

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