Stephen P. Yoon

1.0k total citations
27 papers, 543 citations indexed

About

Stephen P. Yoon is a scholar working on Ophthalmology, Radiology, Nuclear Medicine and Imaging and Neurology. According to data from OpenAlex, Stephen P. Yoon has authored 27 papers receiving a total of 543 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Ophthalmology, 15 papers in Radiology, Nuclear Medicine and Imaging and 3 papers in Neurology. Recurrent topics in Stephen P. Yoon's work include Retinal Diseases and Treatments (13 papers), Retinal Imaging and Analysis (12 papers) and Glaucoma and retinal disorders (11 papers). Stephen P. Yoon is often cited by papers focused on Retinal Diseases and Treatments (13 papers), Retinal Imaging and Analysis (12 papers) and Glaucoma and retinal disorders (11 papers). Stephen P. Yoon collaborates with scholars based in United States, Singapore and United Kingdom. Stephen P. Yoon's co-authors include Sharon Fekrat, Dilraj S. Grewal, Bryce W. Polascik, Atalie C. Thompson, James R. Burke, Cason B. Robbins, Srinath Soundararajan, B.L. Scott, Rupesh Agrawal and Andy Liu and has published in prestigious journals such as SHILAP Revista de lepidopterología, American Journal of Ophthalmology and Investigative Ophthalmology & Visual Science.

In The Last Decade

Stephen P. Yoon

25 papers receiving 530 citations

Peers

Stephen P. Yoon
Cason B. Robbins United States
Stephen P. Yoon
Citations per year, relative to Stephen P. Yoon Stephen P. Yoon (= 1×) peers Cason B. Robbins

Countries citing papers authored by Stephen P. Yoon

Since Specialization
Citations

This map shows the geographic impact of Stephen P. Yoon's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Stephen P. Yoon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stephen P. Yoon more than expected).

Fields of papers citing papers by Stephen P. Yoon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Stephen P. Yoon. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Stephen P. Yoon. The network helps show where Stephen P. Yoon may publish in the future.

Co-authorship network of co-authors of Stephen P. Yoon

This figure shows the co-authorship network connecting the top 25 collaborators of Stephen P. Yoon. A scholar is included among the top collaborators of Stephen P. Yoon based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Stephen P. Yoon. Stephen P. Yoon is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Yoon, Stephen P., Zhiyuan Yu, Stephen C. Pflugfelder, & Cintia S. de Paiva. (2023). Differentially Expressed Tear Proteins in Sjögren's Syndrome Keratoconjunctivitis Sicca. Translational Vision Science & Technology. 12(6). 8–8. 6 indexed citations
2.
Huang, Austin, et al.. (2023). Trends in Residency Academic Productivity of Ophthalmic Plastic and Reconstructive Surgery Fellows Between 2012 and 2019. Ophthalmic Plastic and Reconstructive Surgery. 39(4). 361–365.
3.
Robbins, Cason B., Dilraj S. Grewal, Atalie C. Thompson, et al.. (2021). Identifying Peripapillary Radial Capillary Plexus Alterations in Parkinson’s Disease Using OCT Angiography. Ophthalmology Retina. 6(1). 29–36. 23 indexed citations
4.
Robbins, Cason B., Dilraj S. Grewal, Atalie C. Thompson, et al.. (2020). Repeatability of Peripapillary Optical Coherence Tomography Angiography Parameters in Older Adults. Journal of VitreoRetinal Diseases. 5(3). 239–246. 8 indexed citations
5.
Wisely, C. Ellis, Dong Wang, Ricardo Henao, et al.. (2020). Convolutional neural network to identify symptomatic Alzheimer’s disease using multimodal retinal imaging. British Journal of Ophthalmology. 106(3). 388–395. 80 indexed citations
6.
Robbins, Cason B., Dilraj S. Grewal, Atalie C. Thompson, et al.. (2020). Choroidal Structural Analysis in Alzheimer Disease, Mild Cognitive Impairment, and Cognitively Healthy Controls. American Journal of Ophthalmology. 223. 359–367. 31 indexed citations
7.
Cai, Sophie, Calum Gray, Cason B. Robbins, et al.. (2020). Optical Coherence Tomography Angiography Fractal Dimension in Alzheimer’s Disease, Mild Cognitive Impairment and Cognitively Healthy Controls. Investigative Ophthalmology & Visual Science. 61(7). 5325–5325. 1 indexed citations
8.
Polascik, Bryce W., Atalie C. Thompson, Stephen P. Yoon, et al.. (2020). Association of OCT Angiography Parameters With Age in Cognitively Healthy Older Adults. Ophthalmic surgery, lasers & imaging retina. 51(12). 706–714. 6 indexed citations
9.
Robbins, Cason B., Atalie C. Thompson, Rupesh Agrawal, et al.. (2020). Characterization of Retinal Microvascular and Choroidal Structural Changes in Parkinson Disease. JAMA Ophthalmology. 139(2). 182–182. 106 indexed citations
10.
Wisely, C. Ellis, Dong Wang, Ricardo Henao, et al.. (2019). Deep learning algorithm for diagnosis of Alzheimer’s disease using multimodal retinal imaging. Investigative Ophthalmology & Visual Science. 60(9). 1461–1461. 2 indexed citations
11.
Yoon, Stephen P., Dilraj S. Grewal, Atalie C. Thompson, et al.. (2019). Retinal Microvascular and Neurodegenerative Changes in Alzheimer’s Disease and Mild Cognitive Impairment Compared with Control Participants. Ophthalmology Retina. 3(6). 489–499. 159 indexed citations
12.
Thomas, Akshay S., et al.. (2019). Association of Retinal Inner Layer Disorganization With Ultra-Widefield Fluorescein Angiographic Features and Visual Acuity in Branch Retinal Vein Occlusion. Ophthalmic surgery, lasers & imaging retina. 50(6). 354–364. 9 indexed citations
13.
Thomas, Akshay S., Tahreem A. Mir, Jane S. Kim, et al.. (2019). Impact and Implication of Fovea-Involving Intraretinal Hemorrhage after Acute Branch Retinal Vein Occlusion. Ophthalmology Retina. 3(9). 760–766. 7 indexed citations
14.
Thompson, Atalie C., Stephen P. Yoon, Dilraj S. Grewal, et al.. (2019). Evaluation of potential biomarkers in multimodal retinal images for diagnosis of Parkinson's disease: a pilot study. 60(9). 4565–4565. 1 indexed citations
15.
Mir, Tahreem A., et al.. (2019). Eyes With Acute, Treatment-Naïve CRVO and Foveal Intraretinal Hemorrhage: Characteristics and Outcomes. Ophthalmic surgery, lasers & imaging retina. 50(12). 752–759. 2 indexed citations
16.
Mir, Tahreem A., et al.. (2018). The Impact and Implication of a Fovea-Involving Intraretinal Hemorrhage in Patients with Central Retinal Vein Occlusion. 59(9). 5459–5459. 1 indexed citations
17.
Yoon, Stephen P., et al.. (2018). Bilateral recurrent macular holes. American Journal of Ophthalmology Case Reports. 11. 52–55. 2 indexed citations
18.
Chang, Ken, Stephen P. Yoon, Niral Sheth, et al.. (2015). Rapid vs. delayed infrared responses after ischemia reveal recruitment of different vascular beds. Quantitative InfraRed Thermography Journal. 12(2). 173–183. 6 indexed citations
19.
Liu, Wei‐Min, Ken Chang, Stephen P. Yoon, & Alexander M. Gorbach. (2014). Reconstruction of thermal signals in infrared images reveals sub-cutaneous vasculature and thermogenicity. 1 indexed citations
20.
Weinrich, Sally, et al.. (1998). Predictors of Participation in Prostate Cancer Screening at Worksites. Journal of Community Health Nursing. 15(2). 113–129. 17 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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