Christoph Kern

3.0k total citations · 1 hit paper
36 papers, 1.8k citations indexed

About

Christoph Kern is a scholar working on Ophthalmology, Radiology, Nuclear Medicine and Imaging and Epidemiology. According to data from OpenAlex, Christoph Kern has authored 36 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Ophthalmology, 25 papers in Radiology, Nuclear Medicine and Imaging and 5 papers in Epidemiology. Recurrent topics in Christoph Kern's work include Retinal Diseases and Treatments (17 papers), Retinal Imaging and Analysis (16 papers) and Retinal and Optic Conditions (13 papers). Christoph Kern is often cited by papers focused on Retinal Diseases and Treatments (17 papers), Retinal Imaging and Analysis (16 papers) and Retinal and Optic Conditions (13 papers). Christoph Kern collaborates with scholars based in Germany, United Kingdom and Switzerland. Christoph Kern's co-authors include Pearse A. Keane, Konstantinos Balaskas, Dun Jack Fu, Livia Faes, Siegfried K. Wagner, Gabriella Moraes, Lucas M. Bachmann, Joseph R. Ledsam, Martin Schmid and Alastair K. Denniston and has published in prestigious journals such as Ophthalmology, British Journal of Cancer and American Journal of Ophthalmology.

In The Last Decade

Christoph Kern

32 papers receiving 1.8k citations

Hit Papers

A comparison of deep learning performance against health-... 2019 2026 2021 2023 2019 250 500 750 1000
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.

  1. A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta-analysis
    2019 1.0k citations Xiaoxuan Liu, Livia Faes 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 Career Trend Papers Cites
Christoph Kern Germany 14 983 539 494 449 177 36 1.8k
Dun Jack Fu United Kingdom 17 1.2k 1.2× 675 1.3× 563 1.1× 498 1.1× 138 0.8× 41 2.1k
Gabriella Moraes United Kingdom 12 883 0.9× 375 0.7× 510 1.0× 481 1.1× 101 0.6× 22 1.6k
Livia Faes United Kingdom 20 1.6k 1.6× 1.0k 1.9× 651 1.3× 579 1.3× 176 1.0× 66 2.7k
Avinash V. Varadarajan United States 8 1.1k 1.1× 732 1.4× 219 0.4× 298 0.7× 109 0.6× 10 1.6k
Katy Blumer United States 6 838 0.9× 494 0.9× 215 0.4× 328 0.7× 77 0.4× 8 1.5k
Konstantinos Balaskas United Kingdom 31 2.2k 2.2× 1.9k 3.5× 676 1.4× 590 1.3× 288 1.6× 136 3.8k
Joseph R. Ledsam United Kingdom 8 725 0.7× 85 0.2× 496 1.0× 491 1.1× 142 0.8× 14 1.9k
Aditya U. Kale United Kingdom 6 515 0.5× 116 0.2× 459 0.9× 369 0.8× 66 0.4× 20 1.1k
Alice Bruynseels United Kingdom 6 513 0.5× 109 0.2× 452 0.9× 368 0.8× 60 0.3× 10 1.1k
Edward Korot United Kingdom 14 760 0.8× 550 1.0× 205 0.4× 219 0.5× 75 0.4× 38 1.2k

Countries citing papers authored by Christoph Kern

Since Specialization
Citations

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

Fields of papers citing papers by Christoph Kern

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Christoph Kern

This figure shows the co-authorship network connecting the top 25 collaborators of Christoph Kern. A scholar is included among the top collaborators of Christoph Kern 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 Christoph Kern. Christoph Kern 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.
Holmberg, Olle, Michael Häfner, Tina Herold, et al.. (2024). Evaluation of OCT biomarker changes in treatment-naive neovascular AMD using a deep semantic segmentation algorithm. Eye. 38(16). 3180–3186. 5 indexed citations
2.
Schworm, Benedikt, et al.. (2023). Long-Term Results of 0.19mg Fluocinolone Acetonide Insert for Treatment of Non-Infectious Uveitis in Clinical Practice. Ocular Immunology and Inflammation. 32(7). 1395–1399. 4 indexed citations
3.
Thurau, Stephan, et al.. (2022). Fluocinolone acetonide 0.19-mg implant for the treatment of noninfectious uveitis with involvement of the posterior segment: a real-world study. Graefe s Archive for Clinical and Experimental Ophthalmology. 261(4). 1101–1108. 7 indexed citations
4.
Vounotrypidis, Efstathios, et al.. (2021). Visual outcome after rhegmatogenous retinal detachment repair surgery in patients with multifocal vs monofocal intraocular lenses. Journal of Cataract & Refractive Surgery. 47(12). 1561–1567. 3 indexed citations
5.
Kern, Christoph, Dun Jack Fu, Benedikt Schworm, et al.. (2021). Big data simulations for capacity improvement in a general ophthalmology clinic. Graefe s Archive for Clinical and Experimental Ophthalmology. 259(5). 1289–1296. 8 indexed citations
6.
Kern, Christoph, Dun Jack Fu, Josef Huemer, et al.. (2020). An open-source data set of anti-VEGF therapy in diabetic macular oedema patients over 4 years and their visual acuity outcomes. Eye. 35(5). 1354–1364. 5 indexed citations
7.
Faes, Livia, Dun Jack Fu, Josef Huemer, et al.. (2020). A virtual-clinic pathway for patients referred from a national diabetes eye screening programme reduces service demands whilst maintaining quality of care. Eye. 35(8). 2260–2269. 12 indexed citations
8.
Kern, Christoph & Karsten Kortüm. (2020). [Medial retina clinics in 2030 : A peek into the future].. PubMed. 117(10). 993–998. 1 indexed citations
9.
Schworm, Benedikt, Nikolaus Luft, Christoph Kern, et al.. (2020). Response of neovascular central serous chorioretinopathy to an extended upload of anti-VEGF agents. Graefe s Archive for Clinical and Experimental Ophthalmology. 258(5). 1013–1021. 25 indexed citations
10.
Kern, Christoph, Dun Jack Fu, Benedikt Schworm, et al.. (2020). <p>Two Year Visual Acuity and Structural Outcomes in Patients with Diabetic Macular Oedema Treated with Intravitreal Aflibercept – A Retrospective Cohort Study</p>. Clinical ophthalmology. Volume 14. 533–541. 8 indexed citations
11.
Kern, Christoph, Dun Jack Fu, Karsten Kortuem, et al.. (2019). Implementation of a cloud-based referral platform in ophthalmology: making telemedicine services a reality in eye care. British Journal of Ophthalmology. 104(3). 312–317. 68 indexed citations
12.
Kern, Christoph, Karsten Kortuem, Mehdi Shajari, et al.. (2019). Comparing refractive outcomes of a standard industry toric IOL calculator using anterior corneal astigmatism and total corneal refractive power. Graefe s Archive for Clinical and Experimental Ophthalmology. 258(2). 345–350. 14 indexed citations
13.
Kern, Christoph, Karsten Kortuem, Robin Hamilton, et al.. (2019). Clinical Outcomes of a Hospital-Based Teleophthalmology Service. Ophthalmology Retina. 3(5). 422–428. 32 indexed citations
14.
Liu, Xiaoxuan, Livia Faes, Aditya U. Kale, et al.. (2019). A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta-analysis. The Lancet Digital Health. 1(6). e271–e297. 1020 indexed citations breakdown →
15.
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
16.
Mayer, Wolfgang J., Thomas C. Kreutzer, Martin Dirisamer, et al.. (2017). Comparison of visual outcomes, alignment accuracy, and surgical time between 2 methods of corneal marking for toric intraocular lens implantation. Journal of Cataract & Refractive Surgery. 43(10). 1281–1286. 44 indexed citations
17.
Kortüm, Karsten, Michael Müller, Christoph Kern, et al.. (2017). Using Electronic Health Records to Build an Ophthalmologic Data Warehouse and Visualize Patients' Data. American Journal of Ophthalmology. 178. 84–93. 26 indexed citations
18.
Kortüm, Karsten, Michael Müller, Christoph Hirneiß, et al.. (2016). „Smart eye data“. Der Ophthalmologe. 113(6). 469–477. 11 indexed citations
19.
Haas, Michael, Christoph Kern, Stephan Krüger, et al.. (2014). Assessing novel prognostic serum biomarkers in advanced pancreatic cancer: the role of CYFRA 21-1, serum amyloid A, haptoglobin, and 25-OH vitamin D3. Tumor Biology. 36(4). 2631–2640. 12 indexed citations
20.
Boeck, Stefan, Volker Heinemann, Michael Haas, et al.. (2013). Cytokeratin 19-fragments (CYFRA 21-1) as a novel serum biomarker for response and survival in patients with advanced pancreatic cancer. British Journal of Cancer. 108(8). 1684–1694. 46 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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