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.
FEEDBACK ON A PUBLICLY DISTRIBUTED IMAGE DATABASE: THE MESSIDOR DATABASE
This map shows the geographic impact of Bruno Laÿ'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 Bruno Laÿ with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bruno Laÿ more than expected).
This network shows the impact of papers produced by Bruno Laÿ. 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 Bruno Laÿ. The network helps show where Bruno Laÿ may publish in the future.
Co-authorship network of co-authors of Bruno Laÿ
This figure shows the co-authorship network connecting the top 25 collaborators of Bruno Laÿ.
A scholar is included among the top collaborators of Bruno Laÿ 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 Bruno Laÿ. Bruno Laÿ is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Laÿ, Bruno, Ronan Danno, Gwenolé Quellec, et al.. (2020). Using Artificial Intelligence to detect glaucoma and Age related Macula Degeneration. Investigative Ophthalmology & Visual Science. 61(7). 1647–1647.1 indexed citations
4.
Normand, Guillaume, Gwenolé Quellec, Ronan Danno, et al.. (2019). Prediction of Geographic Atrophy progression by deep learning applied to retinal imaging. 60(9). 1452–1452.2 indexed citations
Laÿ, Bruno, et al.. (2018). Repeatability and Validation of Scheimpflug Scleral Data. 59(9). 1774–1774.3 indexed citations
7.
Laÿ, Bruno, et al.. (2017). Topographic Elevation Data to Design Scleral Lenses. 58(8). 3550–3550.1 indexed citations
8.
Laÿ, Bruno, et al.. (2017). Modeling the limbus as an elliptical toric to optimize scleral lens fitting. 58(8). 3080–3080.1 indexed citations
9.
Laÿ, Bruno, et al.. (2016). Using Corneal elevation specific technology to anti-aberrate a contact lens. Investigative Ophthalmology & Visual Science. 57(12). 1489–1489.1 indexed citations
10.
Laÿ, Bruno, et al.. (2015). Creation of Scleral Lens from Virtual Eye Model. Investigative Ophthalmology & Visual Science. 56(7). 6077–6077.1 indexed citations
Varikooty, Jalaiah, et al.. (2013). The relationship between clinical grading and objective image analysis of Lid Wiper Epitheliopathy. Investigative Ophthalmology & Visual Science. 54(15). 5460–5460.3 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.