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.
Mayo clinical Text Analysis and Knowledge Extraction System (cTAKES): architecture, component evaluation and applications
20101.3k citationsGuergana Savova, James Masanz et al.Journal of the American Medical Informatics Associationprofile →
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 James Masanz'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 James Masanz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James Masanz more than expected).
This network shows the impact of papers produced by James Masanz. 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 James Masanz. The network helps show where James Masanz may publish in the future.
Co-authorship network of co-authors of James Masanz
This figure shows the co-authorship network connecting the top 25 collaborators of James Masanz.
A scholar is included among the top collaborators of James Masanz 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 James Masanz. James Masanz is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Masanz, James, Serguei Pakhomov, Hua Xu, et al.. (2014). Open Source Clinical NLP - More than Any Single System.. PubMed. 2014. 76–82.11 indexed citations
Wu, Stephen, Timothy A. Miller, James Masanz, et al.. (2013). Negation's Not Solved: Reconsidering Negation Annotation and Evaluation..1 indexed citations
5.
Wu, Stephen, James Masanz, K. E. Ravikumar, & Hongfang Liu. (2012). Three Questions About Clinical Information Retrieval.. Text REtrieval Conference.1 indexed citations
6.
Nielsen, Rodney D., James Masanz, James Martin, et al.. (2011). The MiPACQ clinical question answering system.. PubMed. 2011. 171–80.49 indexed citations
7.
Savova, Guergana, James Masanz, Philip V. Ogren, et al.. (2010). Mayo clinical Text Analysis and Knowledge Extraction System (cTAKES): architecture, component evaluation and applications. Journal of the American Medical Informatics Association. 17(5). 507–513.1330 indexed citations breakdown →
8.
Sohn, Sunghwan, Seán Murphy, James Masanz, Jean-Pierre A. Kocher, & Guergana Savova. (2010). Classification of medication status change in clinical narratives.. PubMed. 2010. 762–6.12 indexed citations
Savova, Guergana, Steven Bethard, Will Styler, et al.. (2009). Towards temporal relation discovery from the clinical narrative.. PubMed. 2009. 568–72.45 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.