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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:

Can machine learning improve patient selection for cardiac resynchronization therapy?
Szu-Yeu Hu, Enrico Santus, Alexander W. Forsyth, et al.
PLoS ONE (2019) Vol. 14, Iss. 10, pp. e0222397-e0222397
Open Access | Times Cited: 30

Showing 1-25 of 30 citing articles:

Artificial Intelligence and Machine Learning in Arrhythmias and Cardiac Electrophysiology
Albert Feeny, Mina K. Chung, Anant Madabhushi, et al.
Circulation Arrhythmia and Electrophysiology (2020) Vol. 13, Iss. 8
Open Access | Times Cited: 161
Applications of artificial intelligence in cardiovascular imaging
Maxime Sermesant, Hervé Delingette, Hubert Cochet, et al.
Nature Reviews Cardiology (2021) Vol. 18, Iss. 8, pp. 600-609
Closed Access | Times Cited: 122
Artificial intelligence in the diagnosis and management of arrhythmias
Venkat D. Nagarajan, Lee Su-Lin, Jan‐Lukas Robertus, et al.
European Heart Journal (2021) Vol. 42, Iss. 38, pp. 3904-3916
Open Access | Times Cited: 89
Systematic review of current natural language processing methods and applications in cardiology
Meghan Reading Turchioe, Alexander Volodarskiy, Jyotishman Pathak, et al.
Heart (2021) Vol. 108, Iss. 12, pp. 909-916
Open Access | Times Cited: 77
A multimodal deep learning model for cardiac resynchronisation therapy response prediction
Esther Puyol‐Antón, Baldeep S. Sidhu, Justin Gould, et al.
Medical Image Analysis (2022) Vol. 79, pp. 102465-102465
Open Access | Times Cited: 29
The path from big data analytics capabilities to value in hospitals: a scoping review
Pierre-Yves Brossard, Étienne Minvielle, Claude Sicotte
BMC Health Services Research (2022) Vol. 22, Iss. 1
Open Access | Times Cited: 25
Artificial Intelligence–Aided Precision Medicine for COVID-19: Strategic Areas of Research and Development
Enrico Santus, Nicola Marino, Davide Cirillo, et al.
Journal of Medical Internet Research (2021) Vol. 23, Iss. 3, pp. e22453-e22453
Open Access | Times Cited: 28
Machine Learning for Multimodal Electronic Health Records-Based Research: Challenges and Perspectives
Ziyi Liu, Jiaqi Zhang, Yongshuai Hou, et al.
Communications in computer and information science (2023), pp. 135-155
Closed Access | Times Cited: 11
Cardiovascular Imaging and Intervention Through the Lens of Artificial Intelligence
Karthik Seetharam, Sirish Shrestha, Partho P. Sengupta
Interventional Cardiology Reviews Research Resources (2021) Vol. 16
Open Access | Times Cited: 22
Contemporary Applications of Machine Learning for Device Therapy in Heart Failure
Nitesh Gautam, Sai Nikhila Ghanta, Alex Clausen, et al.
JACC Heart Failure (2022) Vol. 10, Iss. 9, pp. 603-622
Open Access | Times Cited: 16
Artificial intelligence models in prediction of response to cardiac resynchronization therapy: a systematic review
Wojciech Nazar, Stanisław Szymanowicz, Krzysztof Nazar, et al.
Heart Failure Reviews (2023) Vol. 29, Iss. 1, pp. 133-150
Open Access | Times Cited: 9
Machine Learning Prediction of Cardiac Resynchronisation Therapy Response From Combination of Clinical and Model-Driven Data
Svyatoslav Khamzin, Arsenii Dokuchaev, Anastasia Bazhutina, et al.
Frontiers in Physiology (2021) Vol. 12
Open Access | Times Cited: 19
Using Machine-Learning for Prediction of the Response to Cardiac Resynchronization Therapy
Stacey J. Howell, Tim Stivland, Kenneth M. Steín, et al.
JACC. Clinical electrophysiology (2021) Vol. 7, Iss. 12, pp. 1505-1515
Open Access | Times Cited: 18
Shared Decision Making in the Geriatric Surgery Verification Program: Assessing Baseline Performance
Jocelyn Streid, Katherine C. Lee, Angela M. Bader, et al.
Journal of Pain and Symptom Management (2023) Vol. 65, Iss. 6, pp. 510-520.e3
Closed Access | Times Cited: 6
Combination of personalized computational modeling and machine learning for optimization of left ventricular pacing site in cardiac resynchronization therapy
Arsenii Dokuchaev, Tatiana Chumarnaya, Anastasia Bazhutina, et al.
Frontiers in Physiology (2023) Vol. 14
Open Access | Times Cited: 6
Clinical Utility of Body Surface Potential Mapping in CRT Patients
Ksenia Sedova, Kirill Repin, Gleb Donin, et al.
Arrhythmia & Electrophysiology Review (2021) Vol. 10, Iss. 2, pp. 113-119
Open Access | Times Cited: 10
Interpretable machine learning predicts cardiac resynchronization therapy responses from personalized biochemical and biomechanical features
Anamul Haque, Doug Stubbs, Nina Hubig, et al.
BMC Medical Informatics and Decision Making (2022) Vol. 22, Iss. 1
Open Access | Times Cited: 7
Artificial Intelligence: A Shifting Paradigm in Cardio-Cerebrovascular Medicine
Vida Abedi, Seyed‐Mostafa Razavi, Ayesha Khan, et al.
Journal of Clinical Medicine (2021) Vol. 10, Iss. 23, pp. 5710-5710
Open Access | Times Cited: 8
Using machine learning for the personalised prediction of revision endoscopic sinus surgery
Mikko Nuutinen, Jari Haukka, Paula Virkkula, et al.
PLoS ONE (2022) Vol. 17, Iss. 4, pp. e0267146-e0267146
Open Access | Times Cited: 6
Role of Digital Health During Coronavirus Disease 2019 Pandemic and Future Perspectives
Adnan Ahmed, Rishi Charate, Naga Venkata K. Pothineni, et al.
Cardiac Electrophysiology Clinics (2021) Vol. 14, Iss. 1, pp. 115-123
Open Access | Times Cited: 7
Echocardiographic view and feature selection for the estimation of the response to CRT
Alban Gallard, Elena Galli, Arnaud Hubert, et al.
PLoS ONE (2021) Vol. 16, Iss. 6, pp. e0252857-e0252857
Open Access | Times Cited: 6
The ongoing quest for improving machine learning-based risk stratification
Márton Tokodi, Walter Richárd Schwertner, Annamária Kosztin, et al.
European Heart Journal (2020) Vol. 41, Iss. 30, pp. 2914-2915
Open Access | Times Cited: 5
Using Machine-Learning for Prediction of the Response to Cardiac Resynchronization Therapy: the SMART-AV Study
Stacey J. Howell, Tim Stivland, Kenneth M. Steín, et al.
medRxiv (Cold Spring Harbor Laboratory) (2020)
Open Access | Times Cited: 5
Big Data, Small Vessels
L Malin Overmars
(2024)
Open Access
Clinical Features and Physiological Signals Fusion Network for Mechanical Circulatory Support Need Prediction in Pediatric Cardiac Intensive Care Unit
Antonio Mendoza, Sebastian C. Tume, Kriti Puri, et al.
IEEE Journal of Biomedical and Health Informatics (2024) Vol. 29, Iss. 2, pp. 783-791
Closed Access
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