Anne E. Eyler

5.2k total citations · 1 hit paper
9 papers, 1.4k citations indexed

About

Anne E. Eyler is a scholar working on Molecular Biology, Rheumatology and Genetics. According to data from OpenAlex, Anne E. Eyler has authored 9 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 3 papers in Rheumatology and 2 papers in Genetics. Recurrent topics in Anne E. Eyler's work include Biomedical Text Mining and Ontologies (3 papers), Machine Learning in Healthcare (2 papers) and Rheumatoid Arthritis Research and Therapies (2 papers). Anne E. Eyler is often cited by papers focused on Biomedical Text Mining and Ontologies (3 papers), Machine Learning in Healthcare (2 papers) and Rheumatoid Arthritis Research and Therapies (2 papers). Anne E. Eyler collaborates with scholars based in United States. Anne E. Eyler's co-authors include Joshua C. Denny, Robert J. Carroll, Heather E. Wheeler, Eric R. Gamazon, Sahar V. Mozaffari, Hae Kyung Im, Dan L. Nicolae, Keston Aquino-Michaels, Nancy J. Cox and Kaanan P. Shah and has published in prestigious journals such as Nature Genetics, CHEST Journal and The American Journal of Medicine.

In The Last Decade

Anne E. Eyler

8 papers receiving 1.4k citations

Hit Papers

A gene-based association method for mapping traits using ... 2015 2026 2018 2022 2015 250 500 750

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Anne E. Eyler United States 7 782 678 180 97 95 9 1.4k
Kristin Brown‐Gentry United States 14 548 0.7× 648 1.0× 144 0.8× 69 0.7× 89 0.9× 26 1.4k
Lisa A. Bastarache United States 9 309 0.4× 461 0.7× 77 0.4× 49 0.5× 57 0.6× 11 954
Jeffery L. Painter United States 10 525 0.7× 394 0.6× 54 0.3× 72 0.7× 64 0.7× 28 1.3k
Daniel Ziemek United States 18 498 0.6× 134 0.2× 127 0.7× 83 0.9× 144 1.5× 34 1.2k
R Thomas Lumbers United Kingdom 17 481 0.6× 245 0.4× 63 0.3× 60 0.6× 37 0.4× 30 1.3k
Saumya Shekhar Jamuar Singapore 15 325 0.4× 335 0.5× 76 0.4× 93 1.0× 23 0.2× 59 922
Can Yang Hong Kong 19 1.0k 1.3× 1.1k 1.7× 108 0.6× 109 1.1× 76 0.8× 76 1.8k
Nicolas Garcelon France 15 292 0.4× 274 0.4× 176 1.0× 21 0.2× 42 0.4× 84 863
Alex A. Morgan United States 9 1.2k 1.5× 207 0.3× 86 0.5× 166 1.7× 30 0.3× 13 1.7k
Felix Graßmann Germany 25 756 1.0× 232 0.3× 36 0.2× 166 1.7× 57 0.6× 68 1.9k

Countries citing papers authored by Anne E. Eyler

Since Specialization
Citations

This map shows the geographic impact of Anne E. Eyler'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 Anne E. Eyler with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anne E. Eyler more than expected).

Fields of papers citing papers by Anne E. Eyler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Anne E. Eyler. 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 Anne E. Eyler. The network helps show where Anne E. Eyler may publish in the future.

Co-authorship network of co-authors of Anne E. Eyler

This figure shows the co-authorship network connecting the top 25 collaborators of Anne E. Eyler. A scholar is included among the top collaborators of Anne E. Eyler 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 Anne E. Eyler. Anne E. Eyler is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
1.
Carroll, Robert J., Anne E. Eyler, & Joshua C. Denny. (2015). Intelligent use and clinical benefits of electronic health records in rheumatoid arthritis. Expert Review of Clinical Immunology. 11(3). 329–337. 13 indexed citations
2.
Gamazon, Eric R., Heather E. Wheeler, Kaanan P. Shah, et al.. (2015). A gene-based association method for mapping traits using reference transcriptome data. Nature Genetics. 47(9). 1091–1098. 975 indexed citations breakdown →
3.
Eyler, Anne E., et al.. (2014). Magnetic resonance imaging of the cardiac manifestations of Churg-Strauss. JRSM Open. 5(4). 441750458–441750458. 7 indexed citations
4.
Chen, Yukun, Robert J. Carroll, Eugenia McPeek Hinz, et al.. (2013). Applying active learning to high-throughput phenotyping algorithms for electronic health records data. Journal of the American Medical Informatics Association. 20(e2). e253–e259. 82 indexed citations
5.
Carroll, Robert J., Anne E. Eyler, Arthur M. Mandelin, et al.. (2012). Portability of an algorithm to identify rheumatoid arthritis in electronic health records. Journal of the American Medical Informatics Association. 19(e1). e162–e169. 172 indexed citations
6.
Richmond, Bradley W., et al.. (2011). A Tale of Two Rashes. The American Journal of Medicine. 124(5). 414–417.
7.
Carroll, Robert J., Anne E. Eyler, & Joshua C. Denny. (2011). Naïve Electronic Health Record phenotype identification for Rheumatoid arthritis.. PubMed. 2011. 189–96. 87 indexed citations
8.
Byrd, James Brian, Alencia Woodard‐Grice, Elizabeth Stone, et al.. (2010). Association of angiotensin‐converting enzyme inhibitor‐associated angioedema with transplant and immunosuppressant use. Allergy. 65(11). 1381–1387. 33 indexed citations
9.
Slovis, Bonnie & Anne E. Eyler. (2007). A 33-Year-Old Man With Pharyngitis, Transient Rash, and Multiorgan System Failure. CHEST Journal. 132(3). 1080–1083. 1 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.

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