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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:

External validation of a deep learning algorithm for automated echocardiographic strain measurements
Peder L. Myhre, Chung‐Lieh Hung, Matthew Frost, et al.
European Heart Journal - Digital Health (2023) Vol. 5, Iss. 1, pp. 60-68
Open Access | Times Cited: 11

Showing 11 citing articles:

Applications of Artificial Intelligence for the Prediction and Diagnosis of Cancer Therapy-Related Cardiac Dysfunction in Oncology Patients
Isabel G. Scalia, Girish Pathangey, Mahmoud Abdelnabi, et al.
Cancers (2025) Vol. 17, Iss. 4, pp. 605-605
Open Access
The impact of diastolic global longitudinal strain on stroke in patients with acute ischemic stroke
Melis Ozkan, Sefa Tatar, Osman Serhat Tokgöz
Research Square (Research Square) (2025)
Closed Access
Artificial intelligence-assisted left ventricular global longitudinal strain assessment in patients with acute myocardial infarction: a RESUS-AMI trial sub-analysis
Demeke Mekonnen, Ernest Spitzer, Eugène McFadden, et al.
The International Journal of Cardiovascular Imaging (2025)
Closed Access
Deep Learning in Echocardiography for Enhanced Detection of Left Ventricular Function and Wall Motion Abnormalities
Manal Alhussein, M. Liu
Ultrasound in Medicine & Biology (2025)
Closed Access
Ratio of interventricular septal thickness to global longitudinal strain accurately identifies cardiac amyloidosis
Louie Cao, Gloria J. Hong, Michael Abiragi, et al.
Open Heart (2025) Vol. 12, Iss. 1, pp. e003120-e003120
Open Access
Artificial intelligence-derived left ventricular strain in echocardiography in patients treated with chemotherapy
Asuka Kuwahara, Yoichi Iwasaki, Masatake Kobayashi, et al.
The International Journal of Cardiovascular Imaging (2024) Vol. 40, Iss. 9, pp. 1903-1910
Open Access | Times Cited: 3
Machine learning in the prevention of heart failure
Arsalan Hamid, Matthew W. Segar, Biykem Bozkurt, et al.
Heart Failure Reviews (2024)
Closed Access
Beyond Years: Is AI Ready to Predict Biological Age and Cardiovascular Risk Using Echocardiography?
Bjørnar Grenne, Andreas Østvik
Journal of the American Society of Echocardiography (2024) Vol. 37, Iss. 8, pp. 736-739
Closed Access
Concordance of left ventricular volumes and function measurements between two human readers, a fully automated AI algorithm, and the 3D heart model
Peder L. Myhre, Nicola Gaibazzi, Domenico Tuttolomondo, et al.
Frontiers in Cardiovascular Medicine (2024) Vol. 11
Open Access
EchoTracker: Advancing Myocardial Point Tracking in Echocardiography
Md Abulkalam Azad, Artem Chernyshov, John Nyberg, et al.
Lecture notes in computer science (2024), pp. 645-655
Closed Access
Deep learning improves test–retest reproducibility of regional strain in echocardiography
John Nyberg, Andreas Østvik, Ivar Mjåland Salte, et al.
European Heart Journal - Imaging Methods and Practice (2024) Vol. 2, Iss. 4
Open Access
The Role of Artificial Intelligence in Standardising Global Longitudinal Strain Measurements in Echocardiography
Krunoslav Sveric, R Botan, Anna Winkler, et al.
European Heart Journal - Imaging Methods and Practice (2024) Vol. 2, Iss. 4
Open Access
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