Edward Korot

1.9k total citations · 1 hit paper
38 papers, 1.2k citations indexed

About

Edward Korot is a scholar working on Radiology, Nuclear Medicine and Imaging, Ophthalmology and Artificial Intelligence. According to data from OpenAlex, Edward Korot has authored 38 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Radiology, Nuclear Medicine and Imaging, 21 papers in Ophthalmology and 8 papers in Artificial Intelligence. Recurrent topics in Edward Korot's work include Retinal Imaging and Analysis (24 papers), Retinal and Optic Conditions (12 papers) and Retinal Diseases and Treatments (10 papers). Edward Korot is often cited by papers focused on Retinal Imaging and Analysis (24 papers), Retinal and Optic Conditions (12 papers) and Retinal Diseases and Treatments (10 papers). Edward Korot collaborates with scholars based in United Kingdom, United States and Switzerland. Edward Korot's co-authors include Pearse A. Keane, Siegfried K. Wagner, Livia Faes, Xiaoxuan Liu, Alastair K. Denniston, Konstantinos Balaskas, Siddharth Nath, Dun Jack Fu, Nikolas Pontikos and Hagar Khalid and has published in prestigious journals such as Scientific Reports, Ophthalmology and Journal of Medical Internet Research.

In The Last Decade

Edward Korot

37 papers receiving 1.1k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A global review of publicly available datasets for ophthalmological imaging: barriers to access, usability, and generalisability

2020 196 citations Saad Khan, Xiaoxuan Liu et al. The Lancet Digital Health profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Edward Korot United Kingdom	14	760	550	219	205	112	38	1.2k
Naama Hammel United States	16	874 1.1×	814 1.5×	162 0.7×	122 0.6×	112 1.0×	41	1.2k
Neil Joshi United States	13	886 1.2×	668 1.2×	197 0.9×	111 0.5×	230 2.1×	24	1.2k
Avinash V. Varadarajan United States	8	1.1k 1.4×	732 1.3×	298 1.4×	219 1.1×	181 1.6×	10	1.6k
Katy Blumer United States	6	838 1.1×	494 0.9×	328 1.5×	215 1.0×	139 1.2×	8	1.5k
Carson Lam United States	13	606 0.8×	290 0.5×	275 1.3×	92 0.4×	179 1.6×	25	1.1k
Gilbert Lim Singapore	16	1.1k 1.5×	854 1.6×	156 0.7×	150 0.7×	239 2.1×	33	1.4k
Gabriella Moraes United Kingdom	12	883 1.2×	375 0.7×	481 2.2×	510 2.5×	119 1.1×	22	1.6k
An Ran Ran Hong Kong	16	684 0.9×	565 1.0×	101 0.5×	63 0.3×	101 0.9×	41	852
Amir Sadeghipour Austria	15	1.5k 2.0×	1.4k 2.5×	103 0.5×	77 0.4×	182 1.6×	43	1.8k
Aditya U. Kale United Kingdom	6	515 0.7×	116 0.2×	369 1.7×	459 2.2×	62 0.6×	20	1.1k

Countries citing papers authored by Edward Korot

Since Specialization

Citations

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

Fields of papers citing papers by Edward Korot

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Edward Korot. 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 Edward Korot. The network helps show where Edward Korot may publish in the future.

Co-authorship network of co-authors of Edward Korot

This figure shows the co-authorship network connecting the top 25 collaborators of Edward Korot. A scholar is included among the top collaborators of Edward Korot 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 Edward Korot. Edward Korot is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Thirunavukarasu, Arun James, Kabilan Elangovan, Laura Gutiérrez, et al.. (2023). Democratizing Artificial Intelligence Imaging Analysis With Automated Machine Learning: Tutorial. Journal of Medical Internet Research. 25. e49949–e49949. 17 indexed citations

Nakayama, Luis Filipe, Daniel Ferraz, Edward Korot, et al.. (2023). Image quality assessment of retinal fundus photographs for diabetic retinopathy in the machine learning era: a review. Eye. 38(3). 426–433. 11 indexed citations

Korot, Edward, Josef Huemer, Hagar Khalid, et al.. (2023). Clinician-Driven AI: Code-Free Self-Training on Public Data for Diabetic Retinopathy Referral. JAMA Ophthalmology. 141(11). 1029–1029. 7 indexed citations

Fu, Dun Jack, Gabriella Moraes, Konstantinos Balaskas, et al.. (2022). Evaluating an automated machine learning model that predicts visual acuity outcomes in patients with neovascular age-related macular degeneration. Graefe s Archive for Clinical and Experimental Ophthalmology. 260(8). 2461–2473. 19 indexed citations

Karaca, Irmak, et al.. (2022). Acute iridocyclitis and cystoid macular edema related to kinked Hydrus® Microstent in advanced glaucoma. Saudi Journal of Ophthalmology. 36(4). 390–393. 1 indexed citations

Nath, Siddharth, et al.. (2022). New meaning for NLP: the trials and tribulations of natural language processing with GPT-3 in ophthalmology. British Journal of Ophthalmology. 106(7). 889–892. 82 indexed citations

Wang, Sean K., Edward Korot, Marco H. Ji, et al.. (2022). Modeling absolute zone size in retinopathy of prematurity in relation to axial length. Scientific Reports. 12(1). 4717–4717. 4 indexed citations

Huemer, Josef, Hagar Khalid, Daniel Ferraz, et al.. (2021). Re-evaluating diabetic papillopathy using optical coherence tomography and inner retinal sublayer analysis. Eye. 36(7). 1476–1485. 7 indexed citations

Korot, Edward, Siegfried K. Wagner, Robbert Struyven, et al.. (2021). Investigating the impact of saliency maps on clinician’s confidence in model predictions. Investigative Ophthalmology & Visual Science. 62(8). 2297–2297. 1 indexed citations

10.

Korot, Edward, Daniel Ferraz, Siegfried K. Wagner, et al.. (2021). Code-free deep learning for multi-modality medical image classification. Nature Machine Intelligence. 3(4). 288–298. 115 indexed citations

11.

Wagner, Siegfried K., et al.. (2021). Using the What-if Tool to perform nearest counterfactual analysis on an AutoML model that predicts visual acuity outcomes in patients receiving treatment for wet age-related macular degeneration. Investigative Ophthalmology & Visual Science. 62(8). 291–291. 2 indexed citations

12.

Korot, Edward, et al.. (2021). Exploring the What-If-Tool as a solution for machine learning explainability in clinical practice. Investigative Ophthalmology & Visual Science. 62(8). 79–79. 1 indexed citations

13.

Moraes, Gabriella, Dun Jack Fu, Hagar Khalid, et al.. (2020). Quantitative Analysis of OCT for Neovascular Age-Related Macular Degeneration Using Deep Learning. Ophthalmology. 128(5). 693–705. 94 indexed citations

14.

Balaskas, Konstantinos, Pearse A. Keane, Siegfried K. Wagner, et al.. (2020). Automated classification of Retinopathy of Prematurity RetCam images using the Apple CreateML platform: gradeable versus ungradeable image classification. Investigative Ophthalmology & Visual Science. 61(7). 2026–2026. 1 indexed citations

15.

Zhang, Gongyu, Edward Korot, Reena Chopra, et al.. (2020). Optimising Treatment of Neovascular Age-related Macular Degeneration using Reinforcement Learning. Investigative Ophthalmology & Visual Science. 61(7). 1628–1628. 1 indexed citations

16.

Wagner, Siegfried K., Dun Jack Fu, Livia Faes, et al.. (2020). Insights into Systemic Disease through Retinal Imaging-Based Oculomics. Translational Vision Science & Technology. 9(2). 6–6. 149 indexed citations

17.

Khan, Saad, Xiaoxuan Liu, Siddharth Nath, et al.. (2020). A global review of publicly available datasets for ophthalmological imaging: barriers to access, usability, and generalisability. The Lancet Digital Health. 3(1). e51–e66. 196 indexed citations breakdown →

18.

Korot, Edward, Siegfried K. Wagner, Livia Faes, et al.. (2020). AI building AI: Deep Learning Detection of Referable Diabetic Retinopathy Sans-coding. Investigative Ophthalmology & Visual Science. 61(7). 2025–2025. 2 indexed citations

19.

Faes, Livia, Siegfried K. Wagner, Dun Jack Fu, et al.. (2019). Automated deep learning design for medical image classification by health-care professionals with no coding experience: a feasibility study. The Lancet Digital Health. 1(5). e232–e242. 201 indexed citations

20.

Korot, Edward, Aristomenis Thanos, Bozho Todorich, et al.. (2017). Use of the Avegant Glyph Head-Mounted Virtual Retinal Projection Display to Perform Vitreoretinal Surgery. Journal of VitreoRetinal Diseases. 2(1). 22–25. 6 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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