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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-enabled medical computer vision
Andre Esteva, Katherine Chou, Serena Yeung, et al.
npj Digital Medicine (2021) Vol. 4, Iss. 1
Open Access | Times Cited: 850

Showing 1-25 of 850 citing articles:

Large language models encode clinical knowledge
Karan Singhal, Shekoofeh Azizi, Tao Tu, et al.
Nature (2023) Vol. 620, Iss. 7972, pp. 172-180
Open Access | Times Cited: 1321
Multimodal biomedical AI
Julián Acosta, Guido J. Falcone, Pranav Rajpurkar, et al.
Nature Medicine (2022) Vol. 28, Iss. 9, pp. 1773-1784
Open Access | Times Cited: 562
Artificial Intelligence (AI) and Internet of Medical Things (IoMT) Assisted Biomedical Systems for Intelligent Healthcare
Pandiaraj Manickam, Siva Ananth Mariappan, Sindhu Monica Murugesan, et al.
Biosensors (2022) Vol. 12, Iss. 8, pp. 562-562
Open Access | Times Cited: 349
Metaverse for Healthcare: A Survey on Potential Applications, Challenges and Future Directions
Rajeswari Chengoden, Nancy Victor, Thien Huynh‐The, et al.
IEEE Access (2023) Vol. 11, pp. 12765-12795
Open Access | Times Cited: 309
Spatial profiling technologies illuminate the tumor microenvironment
Ofer Elhanani, Raz Ben-Uri, Leeat Keren
Cancer Cell (2023) Vol. 41, Iss. 3, pp. 404-420
Open Access | Times Cited: 193
Expert-level detection of pathologies from unannotated chest X-ray images via self-supervised learning
Ekin Tiu, Ellie Talius, Pujan R. Patel, et al.
Nature Biomedical Engineering (2022) Vol. 6, Iss. 12, pp. 1399-1406
Open Access | Times Cited: 176
Innovative Materials Science via Machine Learning
Chaochao Gao, Xin Min, Minghao Fang, et al.
Advanced Functional Materials (2021) Vol. 32, Iss. 1
Closed Access | Times Cited: 131
Addressing fairness in artificial intelligence for medical imaging
María Agustina Ricci Lara, Rodrigo Echeveste, Enzo Ferrante
Nature Communications (2022) Vol. 13, Iss. 1
Open Access | Times Cited: 127
Deep learning-based meta-classifier approach for COVID-19 classification using CT scan and chest X-ray images
Vinayakumar Ravi, Harini Narasimhan, Chinmay Chakraborty, et al.
Multimedia Systems (2021) Vol. 28, Iss. 4, pp. 1401-1415
Open Access | Times Cited: 111
CLIP-Driven Universal Model for Organ Segmentation and Tumor Detection
Jie Liu, Yixiao Zhang, Jie-Neng Chen, et al.
2021 IEEE/CVF International Conference on Computer Vision (ICCV) (2023), pp. 21095-21107
Closed Access | Times Cited: 111
Artificial intelligence in nursing and midwifery: A systematic review
Siobhán O’Connor, Yongyang Yan, Friederike J.S. Thilo, et al.
Journal of Clinical Nursing (2022) Vol. 32, Iss. 13-14, pp. 2951-2968
Closed Access | Times Cited: 101
The Current Development of Structural Health Monitoring for Bridges: A Review
Z.C. Deng, Minshui Huang, Neng Wan, et al.
Buildings (2023) Vol. 13, Iss. 6, pp. 1360-1360
Open Access | Times Cited: 96
MICU: Image super-resolution via multi-level information compensation and U-net
Yuantao Chen, Runlong Xia, Kai Yang, et al.
Expert Systems with Applications (2024) Vol. 245, pp. 123111-123111
Closed Access | Times Cited: 93
Fibre-optic sensor and deep learning-based structural health monitoring systems for civil structures: A review
U. M. N. Jayawickrema, H.M.C.M. Herath, N. K. Hettiarachchi, et al.
Measurement (2022) Vol. 199, pp. 111543-111543
Closed Access | Times Cited: 89
Applications of convolutional neural networks for intelligent waste identification and recycling: A review
Ting-Wei Wu, Hua Zhang, Wei Peng, et al.
Resources Conservation and Recycling (2022) Vol. 190, pp. 106813-106813
Closed Access | Times Cited: 89
A Comprehensive Survey on TinyML
Youssef Abadade, Anas Temouden, Hatim Bamoumen, et al.
IEEE Access (2023) Vol. 11, pp. 96892-96922
Open Access | Times Cited: 86
Smart Health
Yin Yang, Keng Siau, Wen Xie, et al.
Journal of Organizational and End User Computing (2022) Vol. 34, Iss. 1, pp. 1-14
Open Access | Times Cited: 85
On the Analyses of Medical Images Using Traditional Machine Learning Techniques and Convolutional Neural Networks
Saeed Iqbal, Adnan N. Qureshi, Jianqiang Li, et al.
Archives of Computational Methods in Engineering (2023) Vol. 30, Iss. 5, pp. 3173-3233
Open Access | Times Cited: 82
Machine Learning for Perovskite Solar Cells and Component Materials: Key Technologies and Prospects
Yiming Liu, Xinyu Tan, Jie Liang, et al.
Advanced Functional Materials (2023) Vol. 33, Iss. 17
Closed Access | Times Cited: 79
Derivation of prognostic contextual histopathological features from whole-slide images of tumours via graph deep learning
Yong‐Ju Lee, Jeong Hwan Park, Sohee Oh, et al.
Nature Biomedical Engineering (2022)
Closed Access | Times Cited: 78
AI-based analysis of oral lesions using novel deep convolutional neural networks for early detection of oral cancer
Kritsasith Warin, Wasit Limprasert, Siriwan Suebnukarn, et al.
PLoS ONE (2022) Vol. 17, Iss. 8, pp. e0273508-e0273508
Open Access | Times Cited: 69
Poisoning Attacks in Federated Learning: A Survey
Geming Xia, Jian Chen, Chaodong Yu, et al.
IEEE Access (2023) Vol. 11, pp. 10708-10722
Open Access | Times Cited: 51
Ignore, Trust, or Negotiate: Understanding Clinician Acceptance of AI-Based Treatment Recommendations in Health Care
Venkatesh Sivaraman, Leigh A. Bukowski, Joel Levin, et al.
(2023), pp. 1-18
Open Access | Times Cited: 51
Exploring the Intersection of Artificial Intelligence and Clinical Healthcare: A Multidisciplinary Review
Celina Silvia Stafie, Irina-Georgeta Șufaru, Cristina Mihaela Ghiciuc, et al.
Diagnostics (2023) Vol. 13, Iss. 12, pp. 1995-1995
Open Access | Times Cited: 50
Anomaly detection for industrial quality assurance: A comparative evaluation of unsupervised deep learning models
Justus Zipfel, Felix Verworner, Marco Fischer, et al.
Computers & Industrial Engineering (2023) Vol. 177, pp. 109045-109045
Open Access | Times Cited: 48
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