Eric Farber‐Eger

2.9k citations
73 papers · 1.3k · h-index 18

Impact in

Papers in

Eric Farber‐Eger

69 papers receiving 1.3k citations

Peers

Eric Farber‐Eger
Comparison fields: 5 of 86
  • Cardiology and Cardiovascular Medicine 553
  • Pulmonary and Respiratory Medicine 545
  • Hepatology 27
  • Rheumatology 49
  • Genetics 31
Replace Vanessa van Empel with:
Vanessa van Empel Netherlands
Mohamed M. Gad United States
Pierluigi Costanzo Italy
Antonio Iglesias del Sol Netherlands
Daisuke Goto Japan
Tolga Sinan Güvenç Türkiye
J.C.W. van de Loo Germany
Yuanhua Yang China
Didier Roulin Switzerland
Randall H. Vagelos United States
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Citations per field
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Citations per year

Countries citing papers authored by Eric Farber‐Eger

Since Specialization
Citations

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

Fields of papers citing papers by Eric Farber‐Eger

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Eric Farber‐Eger. 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 Eric Farber‐Eger. The network helps show where Eric Farber‐Eger may publish in the future.

Co-authors

The 25 scholars most cited alongside Eric Farber‐Eger, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Eric Farber‐Eger Line = papers co-authored together Eric Farber‐Eger links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 73 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016145
2 2017107
3 201895
4 202082
5 201975
6 201870
7 201766
8 202155
9 201849
10 201742
11 201739
12 201637
13 201833
14 201431
15 201525
16 201920
17 201619
18 201417
19
Reducing Clinical Noise for Body Mass Index Measures Due to Unit and Transcription Errors in the Electronic Health Record.
201716
20 201915

About Eric Farber‐Eger

Eric Farber‐Eger is a scholar working on Cardiology and Cardiovascular Medicine, Pulmonary and Respiratory Medicine, Genetics, Epidemiology and Surgery, having authored 73 papers that have together received 1.3k indexed citations. Recurring topics across this work include Pulmonary Hypertension Research and Treatments (16 papers), Genetic Associations and Epidemiology (9 papers), Cardiovascular Function and Risk Factors (9 papers), Heart Failure Treatment and Management (8 papers), Blood Pressure and Hypertension Studies (4 papers), Machine Learning in Healthcare (3 papers), Cardiac Arrest and Resuscitation (3 papers) and Cardiac Valve Diseases and Treatments (3 papers). The work is most often cited by research in Cardiology and Cardiovascular Medicine (553 citations), Pulmonary and Respiratory Medicine (545 citations), Hepatology (27 citations), Rheumatology (49 citations) and Genetics (31 citations). Eric Farber‐Eger has collaborated with scholars based in United States, Germany and Canada. Frequent co-authors include Quinn S. Wells, Evan L. Brittain, Anna R. Hemnes, Meng Xu, Tufik R. Assad, Frank E. Harrell, Dana C. Crawford, Thomas J. Wang, Deepak K. Gupta and Shi Huang. Their work appears in journals such as Journal of the American College of Cardiology, Circulation, Pulmonary Circulation, Journal of the American Heart Association and The American Journal of Cardiology.

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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