Danny Eytan

2.1k citations
49 papers · 1.3k · h-index 17

Impact in

Papers in

Danny Eytan

48 papers receiving 1.3k citations

Peers

Danny Eytan
Comparison fields: 5 of 120
  • Cognitive Neuroscience 707
  • Cellular and Molecular Neuroscience 624
  • Health Informatics 34
  • Cardiology and Cardiovascular Medicine 125
  • Statistical and Nonlinear Physics 70
Replace Theodoros P. Zanos with:
Theodoros P. Zanos United States
Mangor Pedersen Australia
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Rakesh Kumar Sinha India
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Citations per field
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Citations per year

Countries citing papers authored by Danny Eytan

Since Specialization
Citations

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

Fields of papers citing papers by Danny Eytan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 49 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006301
2 2003184
3 201076
4 200857
5 200451
6 202050
7 200436
8 202335
9 201133
10
Towards Understanding ECG Rhythm Classification Using Convolutional Neural Networks and Attention Mappings
201831
11 200131
12 202031
13 201731
14 201029
15 201027
16 202126
17 202018
18
Prediction of Cardiac Arrest from Physiological Signals in the Pediatric ICU
201815
19 201815
20 202115

About Danny Eytan

Danny Eytan is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience, Cardiology and Cardiovascular Medicine, Surgery and Biomedical Engineering, having authored 49 papers that have together received 1.3k indexed citations. Recurring topics across this work include Neural dynamics and brain function (10 papers), Neuroscience and Neuropharmacology Research (7 papers), Neuroscience and Neural Engineering (7 papers), EEG and Brain-Computer Interfaces (7 papers), ECG Monitoring and Analysis (7 papers), Non-Invasive Vital Sign Monitoring (6 papers), Healthcare Technology and Patient Monitoring (5 papers) and Hemodynamic Monitoring and Therapy (3 papers). The work is most often cited by research in Cognitive Neuroscience (707 citations), Cellular and Molecular Neuroscience (624 citations), Health Informatics (34 citations), Cardiology and Cardiovascular Medicine (125 citations) and Statistical and Nonlinear Physics (70 citations). Danny Eytan has collaborated with scholars based in Israel, Canada and United States. Frequent co-authors include Shimon Marom, Naama Brenner, A. Gal, Mjaye Mazwi, Avner Wallach, Peter C. Laussen, Andrew Goodwin, Sebastian D. Goodfellow, Robert Greer and Christoph Zrenner. Their work appears in journals such as Journal of Neuroscience, Pediatric Critical Care Medicine, PLoS Computational Biology, Physiological Measurement and European Journal of Pediatrics.

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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