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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:

Deep-learning cardiac motion analysis for human survival prediction
Ghalib Bello, Timothy J. W. Dawes, Jinming Duan, et al.
Nature Machine Intelligence (2019) Vol. 1, Iss. 2, pp. 95-104
Open Access | Times Cited: 216

Showing 1-25 of 216 citing articles:

A Review of Deep Learning in Medical Imaging: Imaging Traits, Technology Trends, Case Studies With Progress Highlights, and Future Promises
S. Kevin Zhou, Hayit Greenspan, Christos Davatzikos, et al.
Proceedings of the IEEE (2021) Vol. 109, Iss. 5, pp. 820-838
Open Access | Times Cited: 703
Machine learning can predict survival of patients with heart failure from serum creatinine and ejection fraction alone
Davide Chicco, Giuseppe Jurman
BMC Medical Informatics and Decision Making (2020) Vol. 20, Iss. 1
Open Access | Times Cited: 478
A deep learning algorithm using a fully connected sparse autoencoder neural network for landslide susceptibility prediction
Faming Huang, Jing Zhang, Chuangbing Zhou, et al.
Landslides (2019) Vol. 17, Iss. 1, pp. 217-229
Closed Access | Times Cited: 384
Deep learning interpretation of echocardiograms
Amirata Ghorbani, David Ouyang, Abubakar Abid, et al.
npj Digital Medicine (2020) Vol. 3, Iss. 1
Open Access | Times Cited: 371
Deep Learning for Cardiac Image Segmentation: A Review
Chen Chen, Chen Qin, Huaqi Qiu, et al.
Frontiers in Cardiovascular Medicine (2020) Vol. 7
Open Access | Times Cited: 370
Deep learning for cardiovascular medicine: a practical primer
Chayakrit Krittanawong, Kipp W. Johnson, Robert S. Rosenson, et al.
European Heart Journal (2019) Vol. 40, Iss. 25, pp. 2058-2073
Open Access | Times Cited: 297
Fuzzy System Based Medical Image Processing for Brain Disease Prediction
Mandong Hu, Yi Zhong, Shuxuan Xie, et al.
Frontiers in Neuroscience (2021) Vol. 15
Open Access | Times Cited: 258
Artificial intelligence in medical imaging: switching from radiographic pathological data to clinically meaningful endpoints
Ohad Oren, Bernard J. Gersh, Deepak L. Bhatt
The Lancet Digital Health (2020) Vol. 2, Iss. 9, pp. e486-e488
Open Access | Times Cited: 245
Precision medicine in the era of artificial intelligence: implications in chronic disease management
Murugan Subramanian, Anne Wojtusciszyn, Lucie Favre, et al.
Journal of Translational Medicine (2020) Vol. 18, Iss. 1
Open Access | Times Cited: 228
Artificial intelligence and machine learning in precision and genomic medicine
Sameer Quazi
Medical Oncology (2022) Vol. 39, Iss. 8
Open Access | Times Cited: 222
Machine learning in cardiovascular magnetic resonance: basic concepts and applications
Tim Leiner, Daniel Rueckert, Avan Suinesiaputra, et al.
Journal of Cardiovascular Magnetic Resonance (2019) Vol. 21, Iss. 1, pp. 61-61
Open Access | Times Cited: 210
Survey on Deep Neural Networks in Speech and Vision Systems
Mahbubul Alam, Manar D. Samad, Lasitha Vidyaratne, et al.
Neurocomputing (2020) Vol. 417, pp. 302-321
Open Access | Times Cited: 203
Artificial intelligence for precision medicine in neurodevelopmental disorders
Mohammed Uddin, Yujiang Wang, Marc Woodbury‐Smith
npj Digital Medicine (2019) Vol. 2, Iss. 1
Open Access | Times Cited: 196
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: 162
A population-based phenome-wide association study of cardiac and aortic structure and function
Wenjia Bai, Hideaki Suzuki, Jian Huang, et al.
Nature Medicine (2020) Vol. 26, Iss. 10, pp. 1654-1662
Open Access | Times Cited: 162
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: 123
Artificial intelligence and machine learning in precision medicine: A paradigm shift in big data analysis
Mehar Sahu, Rohan Gupta, Rashmi K. Ambasta, et al.
Progress in molecular biology and translational science (2022), pp. 57-100
Closed Access | Times Cited: 94
Guidelines and evaluation of clinical explainable AI in medical image analysis
Weina Jin, Xiaoxiao Li, Mostafa Fatehi, et al.
Medical Image Analysis (2022) Vol. 84, pp. 102684-102684
Open Access | Times Cited: 91
Multi-task deep learning for medical image computing and analysis: A review
Yan Zhao, Xiuying Wang, Tongtong Che, et al.
Computers in Biology and Medicine (2022) Vol. 153, pp. 106496-106496
Closed Access | Times Cited: 83
Artificial intelligence in healthcare: A bibliometric analysis
Bahiru Legesse Jimma
Telematics and Informatics Reports (2023) Vol. 9, pp. 100041-100041
Open Access | Times Cited: 64
Spike-driven multi-scale learning with hybrid mechanisms of spiking dendrites
Shuangming Yang, Yanwei Pang, Haowen Wang, et al.
Neurocomputing (2023) Vol. 542, pp. 126240-126240
Closed Access | Times Cited: 55
Present and Future Innovations in AI and Cardiac MRI
Manuel A. Morales, Warren J. Manning, Reza Nezafat
Radiology (2024) Vol. 310, Iss. 1
Closed Access | Times Cited: 29
Bias in Cross-Entropy-Based Training of Deep Survival Networks
Shekoufeh Gorgi Zadeh, Matthias Schmid
IEEE Transactions on Pattern Analysis and Machine Intelligence (2020) Vol. 43, Iss. 9, pp. 3126-3137
Closed Access | Times Cited: 110
An artificial intelligence framework for automatic segmentation and volumetry of vestibular schwannomas from contrast-enhanced T1-weighted and high-resolution T2-weighted MRI
Jonathan Shapey, Guotai Wang, Reuben Dorent, et al.
Journal of neurosurgery (2019) Vol. 134, Iss. 1, pp. 171-179
Closed Access | Times Cited: 102
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