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.
The ClinicalTrials.gov Results Database — Update and Key Issues
2011547 citationsDeborah A. Zarin, Tony Tse et al.New England Journal of Medicineprofile →
Citations per year, relative to Nicholas C. Ide Nicholas C. Ide (= 1×)
peers
Rebecca J. Williams
Countries citing papers authored by Nicholas C. Ide
Since
Specialization
Citations
This map shows the geographic impact of Nicholas C. Ide'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 Nicholas C. Ide with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nicholas C. Ide more than expected).
This network shows the impact of papers produced by Nicholas C. Ide. 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 Nicholas C. Ide. The network helps show where Nicholas C. Ide may publish in the future.
Co-authorship network of co-authors of Nicholas C. Ide
This figure shows the co-authorship network connecting the top 25 collaborators of Nicholas C. Ide.
A scholar is included among the top collaborators of Nicholas C. Ide 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 Nicholas C. Ide. Nicholas C. Ide is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
12 of 12 papers shown
1.
Demner‐Fushman, Dina, Swapna Abhyankar, Antonio Jimeno Yepes, et al.. (2011). A Knowledge-Based Approach to Medical Records Retrieval.. Text REtrieval Conference.25 indexed citations
2.
Zarin, Deborah A., Tony Tse, Rebecca J. Williams, Robert M. Califf, & Nicholas C. Ide. (2011). The ClinicalTrials.gov Results Database — Update and Key Issues. New England Journal of Medicine. 364(9). 852–860.547 indexed citations breakdown →
3.
Demner‐Fushman, Dina, Susanne M. Humphrey, Nicholas C. Ide, et al.. (2007). Combining Resources to Find Answers to Biomedical Questions.. Text REtrieval Conference.29 indexed citations
Zarin, Deborah A., Nicholas C. Ide, Tony Tse, William R. Harlan, & Donald A. B. Lindberg. (2007). Clinical Trial Registries—Reply. JAMA. 298(13).2 indexed citations
6.
Demner‐Fushman, Dina, Susanne M. Humphrey, Nicholas C. Ide, et al.. (2006). Finding Relevant Passages in Scientific Articles: Fusion of Automatic Approaches vs. an Interactive Team Effort.. Text REtrieval Conference.13 indexed citations
Aronson, Alan R., Susanne M. Humphrey, Nicholas C. Ide, et al.. (2004). Knowledge-Intensive and Statistical Approaches to the Retrieval and Annotation of Genomics MEDLINE Citations.. Text REtrieval Conference.10 indexed citations
Tse, Tony, et al.. (2004). Design, implementation and management of a web-based data entry system for ClinicalTrials.gov.. PubMed. 107(Pt 2). 1466–70.38 indexed citations
11.
Kayaalp, Mehmet, Alan R. Aronson, Susanne M. Humphrey, et al.. (2003). Methods for Accurate Retrieval of MEDLINE Citations in Functional Genomics.. Text REtrieval Conference. 17(3). 441–450.10 indexed citations
12.
McCray, Alexa T., et al.. (2000). Usability issues in developing a Web-based consumer health site.. PubMed. 556–60.23 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.