Giorgio Quer

3.6k citations
70 papers · 2.5k · h-index 24

Impact in

Papers in

Giorgio Quer

69 papers receiving 2.4k citations

Peers

Giorgio Quer
Comparison fields: 5 of 156
  • Health Informatics 228
  • Computer Networks and Communications 552
  • Cardiology and Cardiovascular Medicine 375
  • Health Information Management 79
  • Computational Mechanics 290
Replace Jinseok Lee with:
Jinseok Lee South Korea
Fani Deligianni United Kingdom
R.S.H. Istepanian United Kingdom
Afshin Shoeibi Iran
Lei Clifton United Kingdom
Serena Y. Yeung United States
Amir Masoud Rahmani United States
Charence Wong United Kingdom
Rajib Kumar Rana Australia
Faraz S. Ahmad United States
Giorgio Quer relative to Jinseok Lee South Korea Jinseok Lee's profile →
Citations per field
00.5×2×4×6×8×9.4×
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 70 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020397
2 2020330
3 2021245
4 2012157
5 2020133
6 2009128
7 202174
8 200970
9 202167
10 201758
11 202256
12 202044
13 201141
14 201741
15 202340
16 202138
17 200933
18 202430
19 201329
20 201828

About Giorgio Quer

Giorgio Quer is a scholar working on Cardiology and Cardiovascular Medicine, Computer Networks and Communications, Health Informatics, Signal Processing and Modeling and Simulation, having authored 70 papers that have together received 2.5k 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 (7 papers), Wireless Networks and Protocols (7 papers), ECG Monitoring and Analysis (7 papers), Machine Learning in Healthcare (6 papers), Cooperative Communication and Network Coding (6 papers) and Advanced MIMO Systems Optimization (6 papers). The work is most often cited by research in Health Informatics (228 citations), Computer Networks and Communications (552 citations), Cardiology and Cardiovascular Medicine (375 citations), Health Information Management (79 citations) and Computational Mechanics (290 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, Matteo Gadaleta, Riccardo Masiero, Katie Baca-Motes and Edward Ramos. Their work appears in journals such as npj Digital Medicine, Nature Medicine, The Lancet Digital Health, The Lancet and IEEE Journal of Biomedical and Health Informatics.

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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