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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:

Clinically Feasible and Accurate View Classification of Echocardiographic Images Using Deep Learning
Kenya Kusunose, Akihiro Haga, M. Inoue, et al.
Biomolecules (2020) Vol. 10, Iss. 5, pp. 665-665
Open Access | Times Cited: 70

Showing 1-25 of 70 citing articles:

Automated interpretation of systolic and diastolic function on the echocardiogram: a multicohort study
Jasper Tromp, Paul J Seekings, Chung‐Lieh Hung, et al.
The Lancet Digital Health (2021) Vol. 4, Iss. 1, pp. e46-e54
Open Access | Times Cited: 100
Automated Echocardiographic Detection of Severe Coronary Artery Disease Using Artificial Intelligence
Ross Upton, Angela Mumith, Arian Beqiri, et al.
JACC. Cardiovascular imaging (2021) Vol. 15, Iss. 5, pp. 715-727
Open Access | Times Cited: 80
A formal validation of a deep learning-based automated workflow for the interpretation of the echocardiogram
Jasper Tromp, David JM Bauer, Brian Claggett, et al.
Nature Communications (2022) Vol. 13, Iss. 1
Open Access | Times Cited: 57
Artificial intelligence and heart failure: A state‐of‐the‐art review
Muhammad Shahzeb Khan, Muhammad Sameer Arshad, Stephen J. Greene, et al.
European Journal of Heart Failure (2023) Vol. 25, Iss. 9, pp. 1507-1525
Closed Access | Times Cited: 30
Artificial Intelligence in Heart Failure: Friend or Foe?
Angeliki Bourazana, Αndrew Xanthopoulos, Αlexandros Briasoulis, et al.
Life (2024) Vol. 14, Iss. 1, pp. 145-145
Open Access | Times Cited: 12
Artificial intelligence-based classification of echocardiographic views
Jwan A. Naser, Eunjung Lee, Sorin V. Pislaru, et al.
European Heart Journal - Digital Health (2024) Vol. 5, Iss. 3, pp. 260-269
Open Access | Times Cited: 8
Steps to use artificial intelligence in echocardiography
Kenya Kusunose
Journal of Echocardiography (2020) Vol. 19, Iss. 1, pp. 21-27
Open Access | Times Cited: 56
Automated Analysis of Doppler Echocardiographic Videos as a Screening Tool for Valvular Heart Diseases
Feifei Yang, Xiaotian Chen, Xixiang Lin, et al.
JACC. Cardiovascular imaging (2021) Vol. 15, Iss. 4, pp. 551-563
Open Access | Times Cited: 44
Machine Learning for Pediatric Echocardiographic Mitral Regurgitation Detection
Lindsay A. Edwards, Fei Feng, Mehreen Iqbal, et al.
Journal of the American Society of Echocardiography (2022) Vol. 36, Iss. 1, pp. 96-104.e4
Closed Access | Times Cited: 28
Reducing echocardiographic examination time through routine use of fully automated software: a comparative study of measurement and report creation time
Yukina Hirata, Yuka Nomura, Yoshihito Saijo, et al.
Journal of Echocardiography (2024) Vol. 22, Iss. 3, pp. 162-170
Open Access | Times Cited: 6
Application of Artificial Intelligence for Medical Research
Ryuji Hamamoto
Biomolecules (2021) Vol. 11, Iss. 1, pp. 90-90
Open Access | Times Cited: 36
Artificial Intelligence and Echocardiography
Yeonyee E. Yoon, Sekeun Kim, Hyuk‐Jae Chang
Journal of Cardiovascular Imaging (2021) Vol. 29, Iss. 3, pp. 193-193
Open Access | Times Cited: 36
Artificial intelligence applied to support medical decisions for the automatic analysis of echocardiogram images: A systematic review
Vilson Soares de Siqueira, Moisés Marcos Borges, Rogério Gomes Furtado, et al.
Artificial Intelligence in Medicine (2021) Vol. 120, pp. 102165-102165
Closed Access | Times Cited: 34
Artificial Intelligence in Congenital Heart Disease
Pei‐Ni Jone, Addison Gearhart, Howard Lei, et al.
JACC Advances (2022) Vol. 1, Iss. 5, pp. 100153-100153
Open Access | Times Cited: 27
Revolution of echocardiographic reporting: the new era of artificial intelligence and natural language processing
Kenya Kusunose
Journal of Echocardiography (2023) Vol. 21, Iss. 3, pp. 99-104
Closed Access | Times Cited: 15
Assisted probe guidance in cardiac ultrasound: A review
Sofia Ferraz, Miguel Coimbra, João Pedrosa
Frontiers in Cardiovascular Medicine (2023) Vol. 10
Open Access | Times Cited: 12
Deep learning supported echocardiogram analysis: A comprehensive review
G Sanjeevi, G. Uma, Rahul Krishnan Parthinarupothi, et al.
Artificial Intelligence in Medicine (2024) Vol. 151, pp. 102866-102866
Closed Access | Times Cited: 4
SPEMix: a lightweight method via superclass pseudo-label and efficient mixup for echocardiogram view classification
Shoudong Ma, Yifeng Zhang, Delong Li, et al.
Frontiers in Artificial Intelligence (2025) Vol. 7
Open Access
Progress on mitochondria and hair follicle development in androgenetic alopecia: relationships and therapeutic perspectives
Tingru Dong, Yujie Li, Shiyu Jin, et al.
Stem Cell Research & Therapy (2025) Vol. 16, Iss. 1
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
Echocardiography-based AI for detection and quantification of atrial septal defect
Xixiang Lin, Feifei Yang, Yixin Chen, et al.
Frontiers in Cardiovascular Medicine (2023) Vol. 10
Open Access | Times Cited: 8
How to standardize the measurement of left ventricular ejection fraction
Kenya Kusunose, Robert Zheng, Hirotsugu Yamada, et al.
Journal of Medical Ultrasonics (2021) Vol. 49, Iss. 1, pp. 35-43
Open Access | Times Cited: 18
Echocardiography-based AI detection of regional wall motion abnormalities and quantification of cardiac function in myocardial infarction
Xixiang Lin, Feifei Yang, Yixin Chen, et al.
Frontiers in Cardiovascular Medicine (2022) Vol. 9
Open Access | Times Cited: 13
Deep learning-based approaches for myocardial infarction detection: A comprehensive review recent advances and emerging challenges
Elshafey Radwa, Ridha Hamila, Fayçal Bensaali
Medicine in Novel Technology and Devices (2024) Vol. 23, pp. 100322-100322
Open Access | Times Cited: 2
Deep Learning Analysis of Echocardiographic Images to Predict Positive Genotype in Patients With Hypertrophic Cardiomyopathy
Sae Morita, Kenya Kusunose, Akihiro Haga, et al.
Frontiers in Cardiovascular Medicine (2021) Vol. 8
Open Access | Times Cited: 16
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