Deep learning for cellular image analysis2019 · 737 citations
What are hit papers?
Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if any of the following hold:
it has ≥500 total citations;
it reaches ≥1.5× the top-1% citation threshold for papers in the same subfield and year (the
threshold is the minimum needed to enter the top 1%, not the average within it);
it reaches the top citation threshold in at least one of its specific research topics.
This map shows the geographic impact of Dylan Bannon'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 Dylan Bannon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dylan Bannon more than expected).
This network shows the impact of papers produced by Dylan Bannon. 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 Dylan Bannon. The network helps show where Dylan Bannon may publish in the future.
Co-authorship network
The 14 scholars most cited alongside Dylan Bannon, linked wherever they have
co-authored with each other. Click a name or a connecting line to browse the papers they
share.
Border = papers with Dylan BannonLine = papers co-authored togetherDylan Bannon links everyone, so they are left out of the graph.
Dylan Bannon is a scholar working on Biophysics, Media Technology, Artificial Intelligence, Biomedical Engineering and Molecular Biology, having authored 3 papers that have together received 871 indexed citations. Recurring topics across this work include Cell Image Analysis Techniques (3 papers), Image Processing Techniques and Applications (2 papers), Innovative Microfluidic and Catalytic Techniques Innovation (1 paper), 3D Printing in Biomedical Research (1 paper), Single-cell and spatial transcriptomics (1 paper) and AI in cancer detection (1 paper). The work is most often cited by research in Biophysics (438 citations), Structural Biology (30 citations), Media Technology (159 citations), Health Informatics (10 citations) and Computer Vision and Pattern Recognition (107 citations). Dylan Bannon has collaborated with scholars based in United States. Frequent co-authors include David Van Valen, Erick Moen, William D. Graf, Takamasa Kudo, Markus W. Covert, A. Sina Booeshaghi, Eduardo da Veiga Beltrame, Lior Pachter, Jase Gehring and Noah F. Greenwald. Their work appears in journals such as Nature Methods and Scientific Reports.
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.