Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Artificial Intelligence to Detect Papilledema from Ocular Fundus Photographs
Dan Miléa, Raymond P. Najjar, Zhubo Jiang, et al.
New England Journal of Medicine (2020) Vol. 382, Iss. 18, pp. 1687-1695
Open Access | Times Cited: 283

Showing 1-25 of 283 citing articles:

AI in health and medicine
Pranav Rajpurkar, Emma Chen, Oishi Banerjee, et al.
Nature Medicine (2022) Vol. 28, Iss. 1, pp. 31-38
Closed Access | Times Cited: 1414
Artificial Intelligence and Deep Learning in Ophthalmology
Daniel Shu Wei Ting, Louis R. Pasquale, Lily Peng, et al.
Artificial Intelligence in Medicine (2022), pp. 1519-1552
Closed Access | Times Cited: 634
A global review of publicly available datasets for ophthalmological imaging: barriers to access, usability, and generalisability
Saad Khan, Xiaoxuan Liu, Siddharth Nath, et al.
The Lancet Digital Health (2020) Vol. 3, Iss. 1, pp. e51-e66
Open Access | Times Cited: 246
Automatic detection of 39 fundus diseases and conditions in retinal photographs using deep neural networks
Ling‐Ping Cen, Jie Ji, Jianwei Lin, et al.
Nature Communications (2021) Vol. 12, Iss. 1
Open Access | Times Cited: 212
Transforming medical imaging with Transformers? A comparative review of key properties, current progresses, and future perspectives
Jun Li, Junyu Chen, Yucheng Tang, et al.
Medical Image Analysis (2023) Vol. 85, pp. 102762-102762
Open Access | Times Cited: 188
Optical coherence tomography angiography in diabetic retinopathy: an updated review
Zihan Sun, Dawei Yang, Ziqi Tang, et al.
Eye (2020) Vol. 35, Iss. 1, pp. 149-161
Open Access | Times Cited: 150
A deep learning model for detection of Alzheimer's disease based on retinal photographs: a retrospective, multicentre case-control study
Carol Y. Cheung, An Ran Ran, Shujun Wang, et al.
The Lancet Digital Health (2022) Vol. 4, Iss. 11, pp. e806-e815
Open Access | Times Cited: 135
Artificial Intelligence for Screening of Multiple Retinal and Optic Nerve Diseases
Li Dong, Wanji He, Ruiheng Zhang, et al.
JAMA Network Open (2022) Vol. 5, Iss. 5, pp. e229960-e229960
Open Access | Times Cited: 85
Artificial intelligence and deep learning in ophthalmology: Current status and future perspectives
Kai Jin, Juan Ye
Advances in Ophthalmology Practice and Research (2022) Vol. 2, Iss. 3, pp. 100078-100078
Open Access | Times Cited: 75
The promise of digital healthcare technologies
Andy Wai Kan Yeung, Ali Torkamani, Atul J. Butte, et al.
Frontiers in Public Health (2023) Vol. 11
Open Access | Times Cited: 68
Artificial intelligence in ophthalmology: The path to the real-world clinic
Zhongwen Li, Lei Wang, Xuefang Wu, et al.
Cell Reports Medicine (2023) Vol. 4, Iss. 7, pp. 101095-101095
Open Access | Times Cited: 61
From machine learning to deep learning: Advances of the recent data-driven paradigm shift in medicine and healthcare
Chiranjib Chakraborty, Manojit Bhattacharya, Soumen Pal, et al.
Current Research in Biotechnology (2023) Vol. 7, pp. 100164-100164
Open Access | Times Cited: 61
Artificial intelligence and radiologists in prostate cancer detection on MRI (PI-CAI): an international, paired, non-inferiority, confirmatory study
Anindo Saha, Joeran Sander Bosma, Jasper Jonathan Twilt, et al.
The Lancet Oncology (2024) Vol. 25, Iss. 7, pp. 879-887
Closed Access | Times Cited: 44
Utility of artificial intelligence‐based large language models in ophthalmic care
Sayantan Biswas, Leon N. Davies, Amy L. Sheppard, et al.
Ophthalmic and Physiological Optics (2024) Vol. 44, Iss. 3, pp. 641-671
Open Access | Times Cited: 30
Rapid implementation of virtual neurology in response to the COVID-19 pandemic
Scott N. Grossman, Steve C. Han, Laura J. Balcer, et al.
Neurology (2020) Vol. 94, Iss. 24, pp. 1077-1087
Closed Access | Times Cited: 134
Self-Supervised Feature Learning via Exploiting Multi-Modal Data for Retinal Disease Diagnosis
Xiaomeng Li, Mengyu Jia, Md Tauhidul Islam, et al.
IEEE Transactions on Medical Imaging (2020) Vol. 39, Iss. 12, pp. 4023-4033
Open Access | Times Cited: 111
Artificial intelligence for diabetic retinopathy screening, prediction and management
Dinesh Visva Gunasekeran, Daniel Shu Wei Ting, Gavin Siew Wei Tan, et al.
Current Opinion in Ophthalmology (2020) Vol. 31, Iss. 5, pp. 357-365
Closed Access | Times Cited: 106
Application of Comprehensive Artificial intelligence Retinal Expert (CARE) system: a national real-world evidence study
Duoru Lin, Jianhao Xiong, Congxin Liu, et al.
The Lancet Digital Health (2021) Vol. 3, Iss. 8, pp. e486-e495
Open Access | Times Cited: 102
Machine learning and artificial intelligence in haematology
Roni Shouval, Joshua Fein, Bipin N. Savani, et al.
British Journal of Haematology (2020) Vol. 192, Iss. 2, pp. 239-250
Open Access | Times Cited: 97
Artificial Intelligence to Identify Arthroplasty Implants From Radiographs of the Hip
Jaret M. Karnuta, Heather S. Haeberle, Bryan C. Luu, et al.
The Journal of Arthroplasty (2020) Vol. 36, Iss. 7, pp. S290-S294.e1
Closed Access | Times Cited: 86
Deep learning visual analysis in laparoscopic surgery: a systematic review and diagnostic test accuracy meta-analysis
Roi Anteby, Nir Horesh, Shelly Soffer, et al.
Surgical Endoscopy (2021) Vol. 35, Iss. 4, pp. 1521-1533
Closed Access | Times Cited: 85
Rotation-Oriented Collaborative Self-Supervised Learning for Retinal Disease Diagnosis
Xiaomeng Li, Xiaowei Hu, Xiaojuan Qi, et al.
IEEE Transactions on Medical Imaging (2021) Vol. 40, Iss. 9, pp. 2284-2294
Closed Access | Times Cited: 77
Artificial intelligence for the detection of age-related macular degeneration in color fundus photographs: A systematic review and meta-analysis
Li Dong, Qiong Yang, Ruiheng Zhang, et al.
EClinicalMedicine (2021) Vol. 35, pp. 100875-100875
Open Access | Times Cited: 70
Differentiable biology: using deep learning for biophysics-based and data-driven modeling of molecular mechanisms
Mohammed AlQuraishi, Peter K. Sorger
Nature Methods (2021) Vol. 18, Iss. 10, pp. 1169-1180
Open Access | Times Cited: 70
Imaging of the optic nerve: technological advances and future prospects
Valérie Biousse, Helen V. Danesh‐Meyer, Amit M. Saindane, et al.
The Lancet Neurology (2022) Vol. 21, Iss. 12, pp. 1135-1150
Closed Access | Times Cited: 65
Page 1 - Next Page

Scroll to top