Peter H. Scanlon

3.7k total citations · 2 hit papers
66 papers, 2.1k citations indexed

About

Peter H. Scanlon is a scholar working on Ophthalmology, Radiology, Nuclear Medicine and Imaging and Epidemiology. According to data from OpenAlex, Peter H. Scanlon has authored 66 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 60 papers in Ophthalmology, 53 papers in Radiology, Nuclear Medicine and Imaging and 8 papers in Epidemiology. Recurrent topics in Peter H. Scanlon's work include Retinal Diseases and Treatments (56 papers), Retinal Imaging and Analysis (51 papers) and Glaucoma and retinal disorders (25 papers). Peter H. Scanlon is often cited by papers focused on Retinal Diseases and Treatments (56 papers), Retinal Imaging and Analysis (51 papers) and Glaucoma and retinal disorders (25 papers). Peter H. Scanlon collaborates with scholars based in United Kingdom, United States and Italy. Peter H. Scanlon's co-authors include S J Aldington, Irene Stratton, Rafael Simó, Cristina Hernández, Stela Vujosevic, Tünde Pető, Paolo Silva, Raman Malhotra, Chris Foy and Graham Leese and has published in prestigious journals such as The Lancet, Diabetes Care and Ophthalmology.

In The Last Decade

Peter H. Scanlon

62 papers receiving 2.0k citations

Hit Papers

Screening for diabetic retinopathy: new perspectives and ... 2017 2026 2020 2023 2020 2017 100 200 300

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Peter H. Scanlon United Kingdom 22 1.6k 1.5k 245 202 132 66 2.1k
Mukharram M. Bikbov Germany 18 1.5k 0.9× 1.3k 0.9× 374 1.5× 171 0.8× 300 2.3× 140 2.3k
C Alex Harper Australia 26 1.7k 1.0× 1.2k 0.8× 254 1.0× 323 1.6× 366 2.8× 68 2.4k
Brian L. VanderBeek United States 23 1.4k 0.8× 970 0.6× 131 0.5× 167 0.8× 208 1.6× 90 1.9k
Sophie Rogers Australia 23 2.4k 1.5× 1.7k 1.1× 190 0.8× 173 0.9× 168 1.3× 52 3.0k
Muhammad Bayu Sasongko Indonesia 22 1.2k 0.7× 1.1k 0.7× 128 0.5× 153 0.8× 93 0.7× 70 1.6k
S J Aldington United Kingdom 23 2.4k 1.5× 2.2k 1.4× 283 1.2× 530 2.6× 203 1.5× 46 3.1k
Diana Dills United States 10 2.2k 1.3× 1.9k 1.3× 188 0.8× 509 2.5× 319 2.4× 15 3.1k
K C McHardy United Kingdom 18 851 0.5× 930 0.6× 73 0.3× 193 1.0× 92 0.7× 30 1.6k
Vaitheeswaran Kulothungan India 19 619 0.4× 489 0.3× 153 0.6× 214 1.1× 97 0.7× 39 979
M. Rema India 22 837 0.5× 728 0.5× 241 1.0× 765 3.8× 168 1.3× 30 1.9k

Countries citing papers authored by Peter H. Scanlon

Since Specialization
Citations

This map shows the geographic impact of Peter H. Scanlon'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 Peter H. Scanlon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter H. Scanlon more than expected).

Fields of papers citing papers by Peter H. Scanlon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Peter H. Scanlon. 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 Peter H. Scanlon. The network helps show where Peter H. Scanlon may publish in the future.

Co-authorship network of co-authors of Peter H. Scanlon

This figure shows the co-authorship network connecting the top 25 collaborators of Peter H. Scanlon. A scholar is included among the top collaborators of Peter H. Scanlon 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 Peter H. Scanlon. Peter H. Scanlon 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
2.
Scanlon, Peter H., et al.. (2024). The scanning CONfoCal Ophthalmoscopy foR DIAbetic eye screening (CONCORDIA) study paper 2. Eye. 38(18). 3547–3553.
3.
Hernández, Cristina, Olga Simó‐Servat, Massimo Porta, et al.. (2023). Serum glial fibrillary acidic protein and neurofilament light chain as biomarkers of retinal neurodysfunction in early diabetic retinopathy: results of the EUROCONDOR study. Acta Diabetologica. 60(6). 837–844. 7 indexed citations
4.
Stratton, Irene, et al.. (2023). Disengagement and loss to follow-up in intravitreal injection clinics for neovascular age-related macular degeneration. Eye. 37(15). 3186–3190. 5 indexed citations
5.
Sivaprasad, Sobha, Faruque Ghanchi, Simon P. Kelly, et al.. (2023). Evaluation of care with intravitreal aflibercept treatment for UK patients with diabetic macular oedema: DRAKO study 24-month real-world outcomes. Eye. 37(13). 2753–2760. 3 indexed citations
6.
Relton, Samuel D., Andrew Lotery, Robert West, et al.. (2022). Associations with baseline visual acuity in 12,414 eyes starting treatment for neovascular AMD. Eye. 37(8). 1652–1658. 2 indexed citations
7.
Sivaprasad, Sobha, Faruque Ghanchi, Simon P. Kelly, et al.. (2021). Evaluation of standard of care intravitreal aflibercept treatment of diabetic macular oedema treatment-naive patients in the UK: DRAKO study 12-month outcomes. Eye. 36(1). 64–71. 7 indexed citations
8.
Lois, Noemi, Jonathan Cook, Ariel Wang, et al.. (2021). Multimodal imaging interpreted by graders to detect re-activation of diabetic eye disease in previously treated patients: the EMERALD diagnostic accuracy study. Health Technology Assessment. 25(32). 1–104. 2 indexed citations
10.
Vujosevic, Stela, José Cunha‐Vaz, João Figueira, et al.. (2021). Standardization of Optical Coherence Tomography Angiography Imaging Biomarkers in Diabetic Retinal Disease. Ophthalmic Research. 64(6). 871–887. 27 indexed citations
11.
Nevill, Clareece R., Irene Stratton, Sonia S. Maruti, et al.. (2021). Epidemiology of moderately severe and severe non-proliferative diabetic retinopathy in South West England. Eye. 36(2). 433–440. 3 indexed citations
12.
Wright, David M., et al.. (2021). Testing the performance of risk prediction models to determine progression to referable diabetic retinopathy in an Irish type 2 diabetes cohort. British Journal of Ophthalmology. 106(8). bjophthalmol–2020. 6 indexed citations
13.
Scanlon, Peter H., Clareece R. Nevill, Irene Stratton, et al.. (2021). Prevalence and incidence of diabetic retinopathy (DR) in the UK population of Gloucestershire. Acta Ophthalmologica. 100(2). e560–e570. 20 indexed citations
14.
Chakravarthy, Usha, Clare Bailey, Peter H. Scanlon, et al.. (2020). Progression from Early/Intermediate to Advanced Forms of Age-Related Macular Degeneration in a Large UK Cohort: Rates and Risk Factors. Ophthalmology Retina. 4(7). 662–672. 43 indexed citations
15.
Lanzetta, Paolo, Valentina Sarao, Peter H. Scanlon, et al.. (2020). Fundamental principles of an effective diabetic retinopathy screening program. Acta Diabetologica. 57(7). 785–798. 40 indexed citations
16.
Egan, Catherine, Louis Bolter, John Anderson, et al.. (2020). Prospective evaluation of an artificial intelligence-enabled algorithm for automated diabetic retinopathy screening of 30 000 patients. British Journal of Ophthalmology. 105(5). 723–728. 120 indexed citations
17.
Hernández, Cristina, Massimo Porta, Francesco Bandello, et al.. (2020). The Usefulness of Serum Biomarkers in the Early Stages of Diabetic Retinopathy: Results of the EUROCONDOR Clinical Trial. Journal of Clinical Medicine. 9(4). 1233–1233. 15 indexed citations
18.
Scanlon, Peter H.. (2019). Update on Screening for Sight-Threatening Diabetic Retinopathy. Ophthalmic Research. 62(4). 218–224. 31 indexed citations
19.
Lois, Noemi, Jonathan Cook, S J Aldington, et al.. (2019). Effectiveness of Multimodal imaging for the Evaluation of Retinal oedema And new vesseLs in Diabetic retinopathy (EMERALD). BMJ Open. 9(6). e027795–e027795. 4 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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