The Visual Display of Quantitative Information2002 · 925 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 Edward Mulrow'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 Mulrow with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Edward Mulrow more than expected).
This network shows the impact of papers produced by Edward Mulrow. 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 Mulrow. The network helps show where Edward Mulrow may publish in the future.
Co-authors
The 5 scholars most cited alongside Edward Mulrow, 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 Edward MulrowLine = papers co-authored togetherEdward Mulrow links everyone, so they are left out of the graph.
Edward Mulrow is a scholar working on Artificial Intelligence, Economics and Econometrics, Statistics and Probability, Health and Computer Vision and Pattern Recognition, having authored 5 papers that have together received 933 indexed citations. Recurring topics across this work include Water resources management and optimization (1 paper), Housing Market and Economics (1 paper), Census and Population Estimation (1 paper), Healthcare Policy and Management (1 paper), Species Distribution and Climate Change (1 paper), Health disparities and outcomes (1 paper), Data Visualization and Analytics (1 paper) and Statistical Methods in Clinical Trials (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (305 citations), Human-Computer Interaction (44 citations), Statistics and Probability (62 citations), Geography, Planning and Development (34 citations) and Information Systems and Management (41 citations). Edward Mulrow has collaborated with scholars based in United States, Israel and Canada. Frequent co-authors include Kirk M. Wolter, Quentin Brummet, Hee-Choon Shin, Heike Hofmann and Fritz Scheuren. Their work appears in journals such as Technometrics, Harvard Data Science Review and Journal of Data Science.
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.