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About the database ScholarIQanswers from OpenAlex & ORCID
How has Stuart Keel's publication output changed over time?
ScholarIQpublication output · 2017–2023
Output grew0% over the shown period — from 1 works in 2017 to 1 in 2023.
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201720182019202120222023
What are the most-cited papers on Stuart Keel?
ScholarIQmost cited works
Efficacy of a Deep Learning System for Detecting Glaucomatous Optic Neuropathy Based on Color Fundus Photographs
Zhixi Li, Yifan He, Stuart Keel, Wei Meng, Robert T. Chang, Mingguang He
Ophthalmology. 2018847 Citations
A survey of clinicians on the use of artificial intelligence in ophthalmology, dermatology, radiology and radiation oncology
Jane Scheetz, Philip Rothschild, Myra B. McGuinness, Xavier Hadoux, H. Peter Soyer, Monika Janda, James J. J. Condon, Luke Oakden‐Rayner, Lyle J. Palmer, Stuart Keel, Peter van Wijngaarden
Scientific Reports. 2021281 CitationsOPEN ACCESS
An Automated Grading System for Detection of Vision-Threatening Referable Diabetic Retinopathy on the Basis of Color Fundus Photographs
Zhixi Li, Stuart Keel, Chi Liu, Yifan He, Wei Meng, Jane Scheetz, Pei Ying Lee, Jonathan E. Shaw, Daniel Shu Wei Ting, Tien Yin Wong, Hugh R. Taylor, Robert T. Chang, Mingguang He
Diabetes Care. 2018264 Citations
Feasibility and patient acceptability of a novel artificial intelligence-based screening model for diabetic retinopathy at endocrinology outpatient services: a pilot study
Stuart Keel, Pei Ying Lee, Jane Scheetz, Zhixi Li, Mark A. Kotowicz, Richard J. MacIsaac, Mingguang He
Scientific Reports. 2018223 CitationsOPEN ACCESS
Visualizing Deep Learning Models for the Detection of Referable Diabetic Retinopathy and Glaucoma
Stuart Keel, Jinrong Wu, Pei Ying Lee, Jane Scheetz, Mingguang He
JAMA Ophthalmology. 2018119 Citations
Related on ScholarIQ
World Health Organization - Pakistan
Institution
Efficacy of a Deep Learning System for Detecting Glaucomatous Optic Neuropathy Based on Color Fundus Photographs
Paper
A survey of clinicians on the use of artificial intelligence in ophthalmology, dermatology, radiology and radiation oncology
Paper
An Automated Grading System for Detection of Vision-Threatening Referable Diabetic Retinopathy on the Basis of Color Fundus Photographs
Paper
Feasibility and patient acceptability of a novel artificial intelligence-based screening model for diabetic retinopathy at endocrinology outpatient services: a pilot study
Paper
Visualizing Deep Learning Models for the Detection of Referable Diabetic Retinopathy and Glaucoma
Paper