Giorgio Quer

3.5k citations
71 papers · 2.4k · h-index 23

Impact in

Papers in

Giorgio Quer

69 papers receiving 2.3k citations

Peers

Giorgio Quer
Comparison fields: 5 of 155
  • Health Informatics 220
  • Computer Networks and Communications 545
  • Cardiology and Cardiovascular Medicine 352
  • Health Information Management 75
  • Computational Mechanics 286
Replace Jinseok Lee with:
Jinseok Lee South Korea
Fani Deligianni United Kingdom
Afshin Shoeibi Iran
R.S.H. Istepanian United Kingdom
Lei Clifton United Kingdom
Charence Wong United Kingdom
Amir M. Rahmani United States
Serena Yeung United States
Daniele Ravì Italy
Hassan Ugail United Kingdom
Giorgio Quer relative to Jinseok Lee South Korea Jinseok Lee's profile →
Citations per field
00.5×9.2×
Jinseok Lee · 1×
Citations per year

Countries citing papers authored by Giorgio Quer

Since Specialization
Citations

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

Fields of papers citing papers by Giorgio Quer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 71 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020364
2 2020320
3 2021228
4 2012154
5 2020130
6 2009125
7 202171
8 200968
9 202164
10 201758
11 202256
12 202043
13 201739
14 202138
15 201138
16 202336
17 200934
18 201329
19 201828
20 201627

About Giorgio Quer

Giorgio Quer is a scholar working on Computer Networks and Communications, Cardiology and Cardiovascular Medicine, Artificial Intelligence, Biomedical Engineering and Electrical and Electronic Engineering, having authored 71 papers that have together received 2.4k indexed citations. Recurring topics across this work include Heart Rate Variability and Autonomic Control (10 papers), Mobile Ad Hoc Networks (8 papers), Distributed Sensor Networks and Detection Algorithms (8 papers), Wireless Networks and Protocols (7 papers), ECG Monitoring and Analysis (7 papers), Sparse and Compressive Sensing Techniques (6 papers), Advanced MIMO Systems Optimization (6 papers) and Cooperative Communication and Network Coding (6 papers). The work is most often cited by research in Health Informatics (220 citations), Computer Networks and Communications (545 citations), Cardiology and Cardiovascular Medicine (352 citations), Health Information Management (75 citations) and Computational Mechanics (286 citations). Giorgio Quer has collaborated with scholars based in United States, Italy and Germany. Frequent co-authors include Eric J. Topol, Steven R. Steinhubl, Michele Zorzi, Rima Arnaout, Michele Rossi, Jennifer M. Radin, Riccardo Masiero, Matteo Gadaleta, Katie Baca-Motes and Edward Ramos. Their work appears in journals such as npj Digital Medicine, Nature Medicine, The Lancet Digital Health, IEEE Transactions on Wireless Communications and JAMA Network Open.

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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