Georg Ferber

1.5k citations
61 papers · 1.1k · h-index 16

Impact in

Papers in

Georg Ferber

59 papers receiving 1.0k citations

Peers

Georg Ferber
Comparison fields: 5 of 88
  • Cardiology and Cardiovascular Medicine 542
  • Statistics and Probability 86
  • Computational Theory and Mathematics 120
  • Molecular Biology 347
  • Pharmacology 78
Replace Meijian Zhou with:
Meijian Zhou United States
William Crumb United States
Anthony A. Fossa United States
Catherine Ortemann‐Renon United States
Karel Van Ammel Belgium
Dolly A. Parasrampuria United States
Ben G. Small United Kingdom
Göran Duker Sweden
John Koerner United States
Daniël M. Jonker Denmark
Georg Ferber relative to Meijian Zhou United States Meijian Zhou's profile →
Citations per field
00.5×2.7×
Meijian Zhou · 1×
Citations per year

Countries citing papers authored by Georg Ferber

Since Specialization
Citations

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

Fields of papers citing papers by Georg Ferber

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Georg Ferber. 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 Georg Ferber. The network helps show where Georg Ferber may publish in the future.

Co-authors

The 25 scholars most cited alongside Georg Ferber, 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 Georg Ferber Line = papers co-authored together Georg Ferber links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 61 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017174
2 2015143
3 201382
4 201362
5 201149
6 201447
7 201342
8 199939
9 201631
10 201930
11 201524
12 201621
13 201821
14 201520
15 201219
16 201216
17 201115
18 201515
19 201515
20 201414

About Georg Ferber

Georg Ferber is a scholar working on Cardiology and Cardiovascular Medicine, Molecular Biology, Cognitive Neuroscience, Computational Theory and Mathematics and Statistics and Probability, having authored 61 papers that have together received 1.1k indexed citations. Recurring topics across this work include Cardiac electrophysiology and arrhythmias (32 papers), Receptor Mechanisms and Signaling (14 papers), EEG and Brain-Computer Interfaces (7 papers), Computational Drug Discovery Methods (5 papers), Statistical Methods in Clinical Trials (5 papers), ECG Monitoring and Analysis (5 papers), Pesticide Residue Analysis and Safety (4 papers) and Ion channel regulation and function (4 papers). The work is most often cited by research in Cardiology and Cardiovascular Medicine (542 citations), Statistics and Probability (86 citations), Computational Theory and Mathematics (120 citations), Molecular Biology (347 citations) and Pharmacology (78 citations). Georg Ferber has collaborated with scholars based in United Kingdom, Switzerland and United States. Frequent co-authors include Jörg Täubel, Börje Darpö, Christine Garnett, Meijian Zhou, Steve Riley, Ulrike Lorch, A. John Camm, Philip T. Sager, Sara Fernandes and Jiang Liu. Their work appears in journals such as The Journal of Clinical Pharmacology, British Journal of Clinical Pharmacology, Annals of Noninvasive Electrocardiology, Neuropsychobiology and Methods of Information in Medicine.

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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