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.
Artificial intelligence in retina
2018521 citationsUrsula Schmidt‐Erfurth, Amir Sadeghipour et al.profile →
Guidelines for the Management of Diabetic Macular Edema by the European Society of Retina Specialists (EURETINA)
2017464 citationsUrsula Schmidt‐Erfurth, Bianca S. Gerendas et al.profile →
Fully Automated Detection and Quantification of Macular Fluid in OCT Using Deep Learning
2017422 citationsThomas Schlegl, Sebastian M. Waldstein et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Bianca S. Gerendas
Since
Specialization
Citations
This map shows the geographic impact of Bianca S. Gerendas'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 Bianca S. Gerendas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bianca S. Gerendas more than expected).
Fields of papers citing papers by Bianca S. Gerendas
This network shows the impact of papers produced by Bianca S. Gerendas. 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 Bianca S. Gerendas. The network helps show where Bianca S. Gerendas may publish in the future.
Co-authorship network of co-authors of Bianca S. Gerendas
This figure shows the co-authorship network connecting the top 25 collaborators of Bianca S. Gerendas.
A scholar is included among the top collaborators of Bianca S. Gerendas 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 Bianca S. Gerendas. Bianca S. Gerendas is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Grechenig, Christoph, Gregor S. Reiter, Sophie Riedl, et al.. (2021). Impact of Residual Subretinal Fluid Volumes on Treatment Outcomes in a SRF-tolerant Treat & Extend Regimen. Investigative Ophthalmology & Visual Science. 62(8). 104–104.2 indexed citations
Bogunović, Hrvoje, John W. Seaman, Philippe Margaron, et al.. (2020). Detection of retinal fluids in OCT scans by an automated deep learning algorithm compared to human expert grading in the HAWK & HARRIER trials. Investigative Ophthalmology & Visual Science. 61(7). 5187–5187.2 indexed citations
Bogunović, Hrvoje, Sebastian M. Waldstein, Amir Sadeghipour, Bianca S. Gerendas, & Ursula Schmidt‐Erfurth. (2018). Artificial intelligence to predict optimal retreatment intervals in treat-and-extend (T&E). Investigative Ophthalmology & Visual Science. 59(9). 1620–1620.3 indexed citations
10.
Seeböck, Philipp, Sebastian M. Waldstein, René Donner, et al.. (2017). Defining disease endophenotypes in neovascular AMD by unsupervised machine learning of large-scale OCT data. Investigative Ophthalmology & Visual Science. 58(8). 56–56.1 indexed citations
11.
Podkowinski, Dominika, Jing Wu, Bianca S. Gerendas, et al.. (2015). The foveal shape is not predictive of visual acuity and treatment response in macular edema due to retinal vein occlusion. Investigative Ophthalmology & Visual Science. 56(7). 5927–5927.1 indexed citations
12.
Wu, Jing, Sebastian M. Waldstein, Bianca S. Gerendas, et al.. (2015). Disease Modelling & Prediction: Automated Fovea Detection as a Key Registration Landmark for Construction of a Population Reference Frame. Investigative Ophthalmology & Visual Science. 56(7). 5917–5917.1 indexed citations
13.
Schlegl, Thomas, Dominika Podkowinski, Sebastian M. Waldstein, et al.. (2015). Automatic segmentation and classification of intraretinal cystoid fluid and subretinal fluid in 3D-OCT using convolutional neural networks. Investigative Ophthalmology & Visual Science. 56(7). 5920–5920.7 indexed citations
14.
Gerendas, Bianca S., Sonja Prager, Gábor Deák, et al.. (2015). Morphological parameters relevant for long-term outcomes during therapy of diabetic macular edema in the RESTORE Extension trial. Investigative Ophthalmology & Visual Science. 56(7). 4686–4686.2 indexed citations
15.
Montuoro, Alessio, Sebastian M. Waldstein, Bianca S. Gerendas, et al.. (2014). Statistical Retinal OCT Appearance Models. Investigative Ophthalmology & Visual Science. 55(13). 4808–4808.4 indexed citations
16.
Gerendas, Bianca S., Christian Simader, Gábor Deák, et al.. (2014). Morphological parameters relevant for visual and anatomic outcomes during anti-VEGF therapy of diabetic macular edema in the RESTORE trial. Investigative Ophthalmology & Visual Science. 55(13). 1791–1791.13 indexed citations
17.
Schmidt‐Erfurth, Ursula, Bianca S. Gerendas, Sebastian M. Waldstein, et al.. (2013). Total Retinal Thickness Using Iowa Reference Algorithm: Measurement Reproducibility in 5 SD-OCT Scanners. Investigative Ophthalmology & Visual Science. 54(15). 5503–5503.1 indexed citations
18.
Gerendas, Bianca S., Sebastian M. Waldstein, Jan Lammer, et al.. (2012). Centerpoint Replotting And Its Effects On Central Retinal Thickness In Four Prevalent SD-OCT Devices. Investigative Ophthalmology & Visual Science. 53(14). 4114–4114.2 indexed citations
19.
Simader, Christian, Alessio Montuoro, Sebastian M. Waldstein, et al.. (2012). Retinal Thickness Measurements with Spectral Domain Optical Coherence Devices from Different Manufacturers in a Reading Center Environment. Investigative Ophthalmology & Visual Science. 53(14). 4067–4067.3 indexed citations
20.
Gerendas, Bianca S., et al.. (2011). Comparability Of Pixel Size In Images Of Different Cameras Of The Same Type Used For Multi-Center Trials At Different Study Sites Evaluated With A New Test Eye (SISPOT). Investigative Ophthalmology & Visual Science. 52(14). 4049–4049.1 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.