Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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 1-25 of 34 citing articles:

Use of Artificial Intelligence in Improving Outcomes in Heart Disease: A Scientific Statement From the American Heart Association
Antonis A. Armoundas, Sanjiv M. Narayan, Donna K. Arnett, et al.
Circulation (2024) Vol. 149, Iss. 14
Open Access | Times Cited: 59
Peripartum Cardiomyopathy
Zoltàn Arany
New England Journal of Medicine (2024) Vol. 390, Iss. 2, pp. 154-164
Closed Access | Times Cited: 36
State-of-the-Art Deep Learning Methods on Electrocardiogram Data: Systematic Review
Georgios Petmezas, Leandros Stefanopoulos, Vassilis Kilintzis, et al.
JMIR Medical Informatics (2022) Vol. 10, Iss. 8, pp. e38454-e38454
Open Access | Times Cited: 57
Cardiovascular Disease Screening in Women: Leveraging Artificial Intelligence and Digital Tools
Demilade Adedinsewo, Amy W. Pollak, Sabrina D. Phillips, et al.
Circulation Research (2022) Vol. 130, Iss. 4, pp. 673-690
Open Access | Times Cited: 53
Artificial Intelligence in Cardiovascular Medicine: Current Insights and Future Prospects
Ikram ul Haq, Karanjot Chhatwal, Krishna Sanaka, et al.
Vascular Health and Risk Management (2022) Vol. Volume 18, pp. 517-528
Open Access | Times Cited: 32
Adopting artificial intelligence in cardiovascular medicine: a scoping review
Hisaki Makimoto, Takahide Kohro
Hypertension Research (2023) Vol. 47, Iss. 3, pp. 685-699
Closed Access | Times Cited: 18
Early Diagnosis of Cardiovascular Diseases in the Era of Artificial Intelligence: An In-Depth Review
Naiela E Almansouri, Mishael Awe, Selvambigay Rajavelu, et al.
Cureus (2024)
Open Access | Times Cited: 8
The year in cardiovascular medicine 2021: digital health and innovation
Panos Vardas, Folkert W. Asselbergs, Maarten van Smeden, et al.
European Heart Journal (2021) Vol. 43, Iss. 4, pp. 271-279
Open Access | Times Cited: 37
The use of artificial intelligence for delivery of essential health services across WHO regions: a scoping review
Joseph Okeibunor, Anelisa Jaca, Chinwe Juliana Iwu, et al.
Frontiers in Public Health (2023) Vol. 11
Open Access | Times Cited: 16
Mitigating Bias in Clinical Machine Learning Models
Julio C. Perez-Downes, Andrew S. Tseng, Keith Mcconn, et al.
Current Treatment Options in Cardiovascular Medicine (2024) Vol. 26, Iss. 3, pp. 29-45
Closed Access | Times Cited: 6
AI-based preeclampsia detection and prediction with electrocardiogram data
Liam Butler, Fatma Güntürkün, Lokesh Chinthala, et al.
Frontiers in Cardiovascular Medicine (2024) Vol. 11
Open Access | Times Cited: 5
An artificial intelligence electrocardiogram analysis for detecting cardiomyopathy in the peripartum period
Ye-Ji Lee, Byungjin Choi, Min Sung Lee, et al.
International Journal of Cardiology (2022) Vol. 352, pp. 72-77
Open Access | Times Cited: 22
Screening for peripartum cardiomyopathies using artificial intelligence in Nigeria (SPEC-AI Nigeria): Clinical trial rationale and design
Demilade Adedinsewo, Andrea Carolina Morales-Lara, Jennifer Dugan, et al.
American Heart Journal (2023) Vol. 261, pp. 64-74
Closed Access | Times Cited: 13
Results of Cardiovascular Testing among Pregnant and Postpartum Persons Undergoing Standardized Cardiovascular Risk Assessment
Afshan B. Hameed, Maryam Tarsa, Ashten Waks, et al.
American Journal of Obstetrics & Gynecology MFM (2025), pp. 101656-101656
Closed Access
A multicenter pragmatic implementation study of AI-ECG-based clinical decision support software to identify low LVEF: Clinical trial design and methods
Francisco López-Jiménez, Heather M. Alger, Zachi I. Attia, et al.
American Heart Journal Plus Cardiology Research and Practice (2025), pp. 100528-100528
Open Access
Development and validation of an electrocardiographic artificial intelligence model for detection of peripartum cardiomyopathy
İbrahi̇m Karabayir, Gianna Wilkie, Turgay Çelik, et al.
American Journal of Obstetrics & Gynecology MFM (2024) Vol. 6, Iss. 4, pp. 101337-101337
Closed Access | Times Cited: 3
Artificial intelligence–based screening for cardiomyopathy in an obstetric population: A pilot study
Demilade Adedinsewo, Andrea Carolina Morales-Lara, Heather Hardway, et al.
Cardiovascular Digital Health Journal (2024) Vol. 5, Iss. 3, pp. 132-140
Open Access | Times Cited: 3
Artificial intelligence guided screening for cardiomyopathies in an obstetric population: a pragmatic randomized clinical trial
Demilade Adedinsewo, Andrea Carolina Morales-Lara, Bosede Bukola Afolabi, et al.
Nature Medicine (2024)
Open Access | Times Cited: 3
An Explainable Deep Learning-Enhanced IoMT Model for Effective Monitoring and Reduction of Maternal Mortality Risks
Sherine Nagy Saleh, Mazen Nabil Elagamy, Yasmine N. M. Saleh, et al.
Future Internet (2024) Vol. 16, Iss. 11, pp. 411-411
Open Access | Times Cited: 3
­­The emerging role of artificial intelligence enabled electrocardiograms in healthcare
Arunashis Sau, Fu Siong Ng
BMJ Medicine (2023) Vol. 2, Iss. 1, pp. e000193-e000193
Open Access | Times Cited: 7
Cardio-obstetrics: a new specialty
Eugene Braunwald
European Heart Journal (2024) Vol. 45, Iss. 18, pp. 1589-1592
Open Access | Times Cited: 2
Machine Learning-Based Box Models for Pregnancy Care and Maternal Mortality Reduction: A Literature Survey
Issac Neha Margret, K. Rajakumar, K. V. Arulalan, et al.
IEEE Access (2024) Vol. 12, pp. 68184-68207
Open Access | Times Cited: 2
Electrocardiogram-based deep learning model to screen peripartum cardiomyopathy
Young Mi Jung, Sora Kang, Jeong Min Son, et al.
American Journal of Obstetrics & Gynecology MFM (2023) Vol. 5, Iss. 12, pp. 101184-101184
Closed Access | Times Cited: 4
Universal Cardiovascular Disease Risk Assessment in Pregnancy
Afshan B. Hameed, Maryam Tarsa, Cornelia Graves, et al.
JACC Advances (2024) Vol. 3, Iss. 8, pp. 101055-101055
Open Access | Times Cited: 1
Artificial Intelligence in Pediatric Electrocardiography: A Comprehensive Review
David M. Leone, Donnchadh O’Sullivan, Katia Bravo Jaimes
Children (2024) Vol. 12, Iss. 1, pp. 25-25
Open Access | Times Cited: 1
Page 1 - Next Page

Scroll to top