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:
Applications of artificial intelligence and machine learning in heart failure
Tauben Averbuch, Kristen Sullivan, Andrew J. Sauer, et al.
European Heart Journal - Digital Health (2022) Vol. 3, Iss. 2, pp. 311-322
Open Access | Times Cited: 66
Tauben Averbuch, Kristen Sullivan, Andrew J. Sauer, et al.
European Heart Journal - Digital Health (2022) Vol. 3, Iss. 2, pp. 311-322
Open Access | Times Cited: 66
Showing 1-25 of 66 citing articles:
Challenges and strategies for wide-scale artificial intelligence (AI) deployment in healthcare practices: A perspective for healthcare organizations
Pouyan Esmaeilzadeh
Artificial Intelligence in Medicine (2024) Vol. 151, pp. 102861-102861
Closed Access | Times Cited: 75
Pouyan Esmaeilzadeh
Artificial Intelligence in Medicine (2024) Vol. 151, pp. 102861-102861
Closed Access | Times Cited: 75
Current and Future Use of Artificial Intelligence in Electrocardiography
Manuel Martínez‐Sellés, Manuel Marina‐Breysse
Journal of Cardiovascular Development and Disease (2023) Vol. 10, Iss. 4, pp. 175-175
Open Access | Times Cited: 58
Manuel Martínez‐Sellés, Manuel Marina‐Breysse
Journal of Cardiovascular Development and Disease (2023) Vol. 10, Iss. 4, pp. 175-175
Open Access | Times Cited: 58
Naxos Disease and Related Cardio-Cutaneous Syndromes
Alexandros Protonotarios, Angeliki Asimaki, Cristina Basso, et al.
JACC Advances (2025) Vol. 4, Iss. 2, pp. 101547-101547
Open Access | Times Cited: 2
Alexandros Protonotarios, Angeliki Asimaki, Cristina Basso, et al.
JACC Advances (2025) Vol. 4, Iss. 2, pp. 101547-101547
Open Access | Times Cited: 2
Prediction of mortality in heart failure by machine learning. Comparison with statistical modeling
Domenico Scrutinio, Federica Amitrano, Pietro Guida, et al.
European Journal of Internal Medicine (2025)
Closed Access | Times Cited: 2
Domenico Scrutinio, Federica Amitrano, Pietro Guida, et al.
European Journal of Internal Medicine (2025)
Closed Access | Times Cited: 2
Applications of artificial intelligence for nursing: has a new era arrived?
Liesbet Van Bulck, Raphaël Couturier, Philip Moons
European Journal of Cardiovascular Nursing (2022) Vol. 22, Iss. 3, pp. e19-e20
Open Access | Times Cited: 40
Liesbet Van Bulck, Raphaël Couturier, Philip Moons
European Journal of Cardiovascular Nursing (2022) Vol. 22, Iss. 3, pp. e19-e20
Open Access | Times Cited: 40
Improving representativeness in trials: a call to action from the Global Cardiovascular Clinical Trialists Forum
Lynaea Filbey, Jie Wei Zhu, Francesca D’Angelo, et al.
European Heart Journal (2023) Vol. 44, Iss. 11, pp. 921-930
Open Access | Times Cited: 39
Lynaea Filbey, Jie Wei Zhu, Francesca D’Angelo, et al.
European Heart Journal (2023) Vol. 44, Iss. 11, pp. 921-930
Open Access | Times Cited: 39
Recent advancements and applications of deep learning in heart failure: Α systematic review
Georgios Petmezas, Vasileios E. Papageorgiou, Vasileios Vassilikos, et al.
Computers in Biology and Medicine (2024) Vol. 176, pp. 108557-108557
Closed Access | Times Cited: 13
Georgios Petmezas, Vasileios E. Papageorgiou, Vasileios Vassilikos, et al.
Computers in Biology and Medicine (2024) Vol. 176, pp. 108557-108557
Closed Access | Times Cited: 13
Bridging gaps and optimizing implementation of guideline-directed medical therapy for heart failure
Izza Shahid, Muhammad Shahzeb Khan, Gregg C. Fonarow, et al.
Progress in Cardiovascular Diseases (2024) Vol. 82, pp. 61-69
Closed Access | Times Cited: 9
Izza Shahid, Muhammad Shahzeb Khan, Gregg C. Fonarow, et al.
Progress in Cardiovascular Diseases (2024) Vol. 82, pp. 61-69
Closed Access | Times Cited: 9
Artificial Intelligence in Healthcare: Perception and Reality
Abidemi O Akinrinmade, Temitayo M Adebile, Chioma Ezuma-Ebong, et al.
Cureus (2023)
Open Access | Times Cited: 22
Abidemi O Akinrinmade, Temitayo M Adebile, Chioma Ezuma-Ebong, et al.
Cureus (2023)
Open Access | Times Cited: 22
Application and Potential of Artificial Intelligence in Heart Failure: Past, Present, and Future
Minjae Yoon, Jin Joo Park, Taeho Hur, et al.
International Journal of Heart Failure (2023) Vol. 6, Iss. 1, pp. 11-11
Open Access | Times Cited: 18
Minjae Yoon, Jin Joo Park, Taeho Hur, et al.
International Journal of Heart Failure (2023) Vol. 6, Iss. 1, pp. 11-11
Open Access | Times Cited: 18
Machine learning and disease prediction in obstetrics
Zara Arain, Stamatina Iliodromiti, Greg Slabaugh, et al.
Current Research in Physiology (2023) Vol. 6, pp. 100099-100099
Open Access | Times Cited: 17
Zara Arain, Stamatina Iliodromiti, Greg Slabaugh, et al.
Current Research in Physiology (2023) Vol. 6, pp. 100099-100099
Open Access | Times Cited: 17
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
Naiela E Almansouri, Mishael Awe, Selvambigay Rajavelu, et al.
Cureus (2024)
Open Access | Times Cited: 8
Interventions to enhance digital health equity in cardiovascular care
Ariana Mihan, Harriette G.C. Van Spall
Nature Medicine (2024) Vol. 30, Iss. 3, pp. 628-630
Closed Access | Times Cited: 7
Ariana Mihan, Harriette G.C. Van Spall
Nature Medicine (2024) Vol. 30, Iss. 3, pp. 628-630
Closed Access | Times Cited: 7
Machine learning–based 30-day readmission prediction models for patients with heart failure: a systematic review
M Yu, Youn‐Jung Son
European Journal of Cardiovascular Nursing (2024) Vol. 23, Iss. 7, pp. 711-719
Closed Access | Times Cited: 7
M Yu, Youn‐Jung Son
European Journal of Cardiovascular Nursing (2024) Vol. 23, Iss. 7, pp. 711-719
Closed Access | Times Cited: 7
Prediction models for heart failure in the community: A systematic review and meta‐analysis
Ramesh Nadarajah, Tanina Younsi, Elizabeth Romer, et al.
European Journal of Heart Failure (2023) Vol. 25, Iss. 10, pp. 1724-1738
Open Access | Times Cited: 16
Ramesh Nadarajah, Tanina Younsi, Elizabeth Romer, et al.
European Journal of Heart Failure (2023) Vol. 25, Iss. 10, pp. 1724-1738
Open Access | Times Cited: 16
Mitigating the risk of artificial intelligence bias in cardiovascular care
Ariana Mihan, Ambarish Pandey, Harriette G.C. Van Spall
The Lancet Digital Health (2024) Vol. 6, Iss. 10, pp. e749-e754
Open Access | Times Cited: 6
Ariana Mihan, Ambarish Pandey, Harriette G.C. Van Spall
The Lancet Digital Health (2024) Vol. 6, Iss. 10, pp. e749-e754
Open Access | Times Cited: 6
Artificial intelligence in cardiology: a peek at the future and the role of ChatGPT in cardiology practice
Cristina Madaudo, Antonio Luca Maria Parlati, Daniela Di Lisi, et al.
Journal of Cardiovascular Medicine (2024) Vol. 25, Iss. 11, pp. 766-771
Closed Access | Times Cited: 4
Cristina Madaudo, Antonio Luca Maria Parlati, Daniela Di Lisi, et al.
Journal of Cardiovascular Medicine (2024) Vol. 25, Iss. 11, pp. 766-771
Closed Access | Times Cited: 4
Interoception, cardiac health, and heart failure: The potential for artificial intelligence (AI )—driven diagnosis and treatment
Mahavir Singh, Anmol Babbarwal, Sathnur Pushpakumar, et al.
Physiological Reports (2025) Vol. 13, Iss. 1
Open Access
Mahavir Singh, Anmol Babbarwal, Sathnur Pushpakumar, et al.
Physiological Reports (2025) Vol. 13, Iss. 1
Open Access
Enhancing Cardiovascular Health Prediction: A Machine Learning Perspective
Ratnam Dodda, Abhishek Reddy Bonam, Srinidhi Sakinala, et al.
Communications in computer and information science (2025), pp. 87-96
Closed Access
Ratnam Dodda, Abhishek Reddy Bonam, Srinidhi Sakinala, et al.
Communications in computer and information science (2025), pp. 87-96
Closed Access
Comment on ‘Associating Factors of Cognitive Frailty Among Older People With Chronic Heart Failure: Based on LASSO ‐Logistic Regression’
Shuo Wang, Guanghui Bai, Zhihui Wang
Journal of Advanced Nursing (2025)
Closed Access
Shuo Wang, Guanghui Bai, Zhihui Wang
Journal of Advanced Nursing (2025)
Closed Access
Prediction of 14-day hospitalization risk in chronic heart failure patients, using interpretable machine learning methods
Alexander Arndt Pasgaard Xylander, Simon Lebech Cichosz, Morten Hasselstrøm Jensen, et al.
Health and Technology (2025)
Open Access
Alexander Arndt Pasgaard Xylander, Simon Lebech Cichosz, Morten Hasselstrøm Jensen, et al.
Health and Technology (2025)
Open Access
CACTUS: An open dataset and framework for automated Cardiac Assessment and Classification of Ultrasound images using deep transfer learning
Hanae Elmekki, Ahmed Alagha, Hani Sami, et al.
Computers in Biology and Medicine (2025) Vol. 190, pp. 110003-110003
Open Access
Hanae Elmekki, Ahmed Alagha, Hani Sami, et al.
Computers in Biology and Medicine (2025) Vol. 190, pp. 110003-110003
Open Access
Artificial Intelligence in Diagnosis of Heart Failure
Yuji Xie, Linyue Zhang, Wei Sun, et al.
Journal of the American Heart Association (2025)
Open Access
Yuji Xie, Linyue Zhang, Wei Sun, et al.
Journal of the American Heart Association (2025)
Open Access
Applications of Artificial Intelligence in Out-of-Hospital Cardiac Arrest: A Systematic Review
Doju Cheriachan, Heet N Desai, Leslie Sangurima, et al.
Cureus (2025)
Open Access
Doju Cheriachan, Heet N Desai, Leslie Sangurima, et al.
Cureus (2025)
Open Access
Smart Bioelectronics for Real-Time Diagnosis and Therapy of Body Organ Functions
Lili Guo, Hin Kiu Lee, Suyoun Oh, et al.
ACS Sensors (2025)
Closed Access
Lili Guo, Hin Kiu Lee, Suyoun Oh, et al.
ACS Sensors (2025)
Closed Access
