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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:

A Systematic Review and Meta-Analysis of Applying Deep Learning in the Prediction of the Risk of Cardiovascular Diseases From Retinal Images
Wenyi Hu, Fabian Yii, Ruiye Chen, et al.
Translational Vision Science & Technology (2023) Vol. 12, Iss. 7, pp. 14-14
Open Access | Times Cited: 14

Showing 14 citing articles:

Development and validation of a deep-learning model to predict 10-year atherosclerotic cardiovascular disease risk from retinal images using the UK Biobank and EyePACS 10K datasets
Ehsan Vaghefi, David Squirrell, Song Yang, et al.
Cardiovascular Digital Health Journal (2024) Vol. 5, Iss. 2, pp. 59-69
Open Access | Times Cited: 12
Real-world feasibility, accuracy and acceptability of automated retinal photography and AI-based cardiovascular disease risk assessment in Australian primary care settings: a pragmatic trial
Wenyi Hu, Zhihong Lin, Malcolm Clark, et al.
npj Digital Medicine (2025) Vol. 8, Iss. 1
Open Access | Times Cited: 1
Standardization and clinical applications of retinal imaging biomarkers for cardiovascular disease: a Roadmap from an NHLBI workshop
Emily Y. Chew, Stephen A. Burns, Alison G. Abraham, et al.
Nature Reviews Cardiology (2024) Vol. 22, Iss. 1, pp. 47-63
Closed Access | Times Cited: 5
Machine learning algorithms for predicting PTSD: a systematic review and meta-analysis
Masoumeh Vali, Hossein Motahari-Nezhad, Levente Kovács, et al.
BMC Medical Informatics and Decision Making (2025) Vol. 25, Iss. 1
Open Access
Integrating Retinal Segmentation Metrics with Machine Learning for Predictions from Mouse SD-OCT Scans
Maide Gözde İnam, Onur İnam, Xiangjun Yang, et al.
Current Eye Research (2025), pp. 1-10
Open Access
Applications of artificial intelligence-assisted retinal imaging in systemic diseases: A literature review
AliM Al-Halafi
Saudi Journal of Ophthalmology (2023) Vol. 37, Iss. 3, pp. 185-192
Open Access | Times Cited: 8
Artificial Intelligence, the Digital Surgeon: Unravelling Its Emerging Footprint in Healthcare – The Narrative Review
Zifang Shang, Varun Chauhan, Kirti Devi, et al.
Journal of Multidisciplinary Healthcare (2024) Vol. Volume 17, pp. 4011-4022
Open Access | Times Cited: 2
Prediction of Cardiovascular Markers and Diseases Using Retinal Fundus Images and Deep Learning: A Systematic Scoping Review
Livie Yumeng Li, Anders Aasted Isaksen, Benjamin Lebiecka-Johansen, et al.
medRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 1
A Multi-Stage Approach for Cardiovascular Risk Assessment from Retinal Images Using an Amalgamation of Deep Learning and Computer Vision Techniques
Deepthi K Prasad, Madhura Prakash M, Meghna S Kulkarni, et al.
Diagnostics (2024) Vol. 14, Iss. 9, pp. 928-928
Open Access | Times Cited: 1
Blood Pressure Predicted From Artificial Intelligence Analysis of Retinal Images Correlates With Future Cardiovascular Events
David Squirrell, Song Yang, Li Xie, et al.
JACC Advances (2024) Vol. 3, Iss. 12, pp. 101410-101410
Open Access | Times Cited: 1
Development and validation of a deep-learning model to predict 10-year ASCVD risk from retinal images using the UK Biobank and EyePACS 10K datasets
Ehsan Vaghefi, David Squirrell, Song Yang, et al.
medRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 2
The clinical evaluation of a widefield lens to expand the field of view in optical coherence tomography (OCT-A)
Fritz Soecknick, Katharina Breher, Zahra Nafar, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access
Prediction of Cardiovascular Markers and Diseases Using Retinal Fundus Images and Deep Learning: A Systematic Scoping Review
Livie Yumeng Li, Anders Aasted Isaksen, Benjamin Lebiecka-Johansen, et al.
European Heart Journal - Digital Health (2024) Vol. 5, Iss. 6, pp. 660-669
Open Access
Systematic review of Internet of medical things for cardiovascular disease prevention among Australian first nations
Khondker Mohammad Zobair, Luke Houghton, Dian Tjondronegoro, et al.
Heliyon (2023) Vol. 9, Iss. 11, pp. e22420-e22420
Open Access | Times Cited: 1
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