Francesco Regazzoni

45 papers receiving 769 citations

Hit Papers

A comprehensive and biophysically detailed computational ...20232026202420252023204060

Peers

Francesco Regazzoni
Comparison fields: 5 of 77
  • Cardiology and Cardiovascular Medicine 439
  • Biomedical Engineering 182
  • Statistical and Nonlinear Physics 168
  • Computational Mechanics 100
  • Radiology, Nuclear Medicine and Imaging 65
Replace Matteo Salvador with:
Matteo Salvador Italy
Pasquale Claudio Africa Italy
Radomí­r Chabiniok United Kingdom
Simone Deparis Switzerland
Simone Pezzuto Switzerland
Tiziano Passerini United States
Christian Wieners Germany
Li Cai China
Toni Lassila United Kingdom
Johan Hoffman Sweden
Francesco Regazzoni relative to Matteo Salvador Italy Matteo Salvador's profile →
Citations per field
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Matteo Salvador · 1×
Citations per year

Countries citing papers authored by Francesco Regazzoni

Since Specialization
Citations

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

Fields of papers citing papers by Francesco Regazzoni

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Francesco Regazzoni

This figure shows the co-authorship network connecting the top 25 collaborators of Francesco Regazzoni. A scholar is included among the top collaborators of Francesco Regazzoni based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Francesco Regazzoni. Francesco Regazzoni is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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Mathematical modeling and machine learning for the numerical simulation of cardiac electromechanics
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About Francesco Regazzoni

Francesco Regazzoni is a scholar working on Cardiology and Cardiovascular Medicine, Statistics, Probability and Uncertainty and Statistical and Nonlinear Physics, having authored 47 papers that have together received 795 indexed citations. Recurring topics across this work include Cardiac electrophysiology and arrhythmias (27 papers), Cardiovascular Function and Risk Factors (24 papers) and Model Reduction and Neural Networks (11 papers). The work is most often cited by research in Cardiology and Cardiovascular Medicine (439 citations), Statistical and Nonlinear Physics (168 citations) and Statistics, Probability and Uncertainty (59 citations). Francesco Regazzoni has collaborated with scholars based in Italy, Switzerland and United States. Frequent co-authors include Alfio Quarteroni, Luca Dede’, Matteo Salvador, Marco Fedele, Pasquale Claudio Africa, Roberto Piersanti, Stefano Pagani, Christian Vergara, Alberto Zingaro and Michele Bucelli. Their work appears in journals such as Nature Communications, The Journal of Physiology and Scientific Reports.

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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