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.
Rationale and design of a large-scale, app-based study to identify cardiac arrhythmias using a smartwatch: The Apple Heart Study
2018277 citationsMintu P. Turakhia, Manisha Desai et al.American Heart Journalprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Todd Ferris'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 Todd Ferris with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Todd Ferris more than expected).
This network shows the impact of papers produced by Todd Ferris. 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 Todd Ferris. The network helps show where Todd Ferris may publish in the future.
Co-authorship network of co-authors of Todd Ferris
This figure shows the co-authorship network connecting the top 25 collaborators of Todd Ferris.
A scholar is included among the top collaborators of Todd Ferris 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 Todd Ferris. Todd Ferris is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Turakhia, Mintu P., Manisha Desai, Haley Hedlin, et al.. (2018). Rationale and design of a large-scale, app-based study to identify cardiac arrhythmias using a smartwatch: The Apple Heart Study. American Heart Journal. 207. 66–75.277 indexed citations breakdown →
Podchiyska, Tanya, et al.. (2010). Managing Medical Vocabulary Updates in a Clinical Data Warehouse: An RxNorm Case Study.. PubMed. 2010. 477–81.4 indexed citations
7.
Podchiyska, Tanya, et al.. (2009). Automated mapping of pharmacy orders from two electronic health record systems to RxNorm within the STRIDE clinical data warehouse.. PubMed. 2009. 244–8.27 indexed citations
8.
Lowe, Henry, et al.. (2009). STRIDE--An integrated standards-based translational research informatics platform.. PubMed. 2009. 391–5.329 indexed citations
9.
Weber, Susan, et al.. (2007). Clinical arrays of laboratory measures, or "clinarrays", built from an electronic health record enable disease subtyping by severity.. PubMed. 115–9.13 indexed citations
Ferris, Todd, Gregory M. Garrison, & Henry Lowe. (2002). A proposed key escrow system for secure patient information disclosure in biomedical research databases.. PubMed. 245–9.11 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.