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.
Automated Identification of Postoperative Complications Within an Electronic Medical Record Using Natural Language Processing
2011346 citationsHarvey J. Murff, Fern FitzHenry et al.JAMAprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Fern FitzHenry
Since
Specialization
Citations
This map shows the geographic impact of Fern FitzHenry'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 Fern FitzHenry with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fern FitzHenry more than expected).
This network shows the impact of papers produced by Fern FitzHenry. 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 Fern FitzHenry. The network helps show where Fern FitzHenry may publish in the future.
Co-authorship network of co-authors of Fern FitzHenry
This figure shows the co-authorship network connecting the top 25 collaborators of Fern FitzHenry.
A scholar is included among the top collaborators of Fern FitzHenry 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 Fern FitzHenry. Fern FitzHenry is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
FitzHenry, Fern, Jason Denton, Jonathan R. Nebeker, et al.. (2015). Transforming the National Department of Veterans Affairs Data Warehouse to the OMOP Common Data Model.. AMIA.1 indexed citations
Reeves, Ruth, Fern FitzHenry, Glenn T. Gobbel, et al.. (2012). Who said it? Establishing professional attribution among authors of Veterans' Electronic Health Records.. PubMed. 2012. 753–62.2 indexed citations
10.
Murff, Harvey J., Fern FitzHenry, Michael E. Matheny, et al.. (2011). Automated Identification of Postoperative Complications Within an Electronic Medical Record Using Natural Language Processing. JAMA. 306(8). 848–55.346 indexed citations breakdown →
Matheny, Michael E., Fern FitzHenry, Theodore Speroff, et al.. (2009). Detection of blood culture bacterial contamination using natural language processing.. PubMed. 2009. 411–5.14 indexed citations
13.
FitzHenry, Fern, et al.. (2008). BCMA evaluation: finding significance in near misses.. PubMed. 943–943.1 indexed citations
FitzHenry, Fern, et al.. (2005). Measuring the quality of medication administration.. PubMed. 955–955.2 indexed citations
17.
Shultz, Edward K., et al.. (2003). Quill: a novel approach to structured reporting.. PubMed. 1074–1074.9 indexed citations
18.
FitzHenry, Fern, et al.. (2003). Return on investment point of service Computerized Provider Charge Entry.. PubMed. 891–891.1 indexed citations
19.
FitzHenry, Fern, et al.. (2002). Implementing outpatient order entry to support medical necessity using the patient's electronic past medical history.. PubMed. 250–4.4 indexed citations
20.
FitzHenry, Fern & Edward K. Shultz. (2000). Health-risk-assessment tools used to predict costs in defined populations.. PubMed. 14(2). 31–57.11 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.