Fernando Scudiero

63 total papers · 1.1k total citations
38 papers, 616 citations indexed

About

Fernando Scudiero is a scholar working on Cardiology and Cardiovascular Medicine, Surgery and Infectious Diseases. According to data from OpenAlex, Fernando Scudiero has authored 38 papers receiving a total of 616 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Cardiology and Cardiovascular Medicine, 14 papers in Surgery and 10 papers in Infectious Diseases. Recurrent topics in Fernando Scudiero's work include COVID-19 Clinical Research Studies (10 papers), Coronary Interventions and Diagnostics (8 papers) and Antiplatelet Therapy and Cardiovascular Diseases (8 papers). Fernando Scudiero is often cited by papers focused on COVID-19 Clinical Research Studies (10 papers), Coronary Interventions and Diagnostics (8 papers) and Antiplatelet Therapy and Cardiovascular Diseases (8 papers). Fernando Scudiero collaborates with scholars based in Italy, France and Switzerland. Fernando Scudiero's co-authors include Angelo Silverio, Marco Di Maio, Guido Parodi, Giovanni Esposito, Vincenzo Russo, Bruno Trimarco, Cinzia Perrino, Emilio Attena, Pierpaolo Di Micco and Gabriele G. Schiattarella and has published in prestigious journals such as European Heart Journal, The American Journal of Cardiology and Frontiers in Pharmacology.

In The Last Decade

Fernando Scudiero

37 papers receiving 612 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Fernando Scudiero	338	202	173	167	147	38	616
Denis Doyen	286 0.8×	196 1.0×	123 0.7×	171 1.0×	65 0.4×	29	574
Vedat Çiçek	296 0.9×	128 0.6×	83 0.5×	47 0.3×	114 0.8×	51	551
Ömer Faruk Baycan	274 0.8×	242 1.2×	131 0.8×	48 0.3×	58 0.4×	32	522
Murat Selçuk	300 0.9×	90 0.4×	62 0.4×	53 0.3×	94 0.6×	54	523
Josanna Rodriguez‐Lopez	193 0.6×	126 0.6×	89 0.5×	196 1.2×	70 0.5×	36	695
Giacomo Ingallina	319 0.9×	125 0.6×	78 0.5×	142 0.9×	101 0.7×	51	508
Nadin Elsayed	178 0.5×	295 1.5×	190 1.1×	254 1.5×	125 0.9×	42	643
Kuldeep Shah	359 1.1×	92 0.5×	45 0.3×	62 0.4×	69 0.5×	47	517
Cesare Baldi	367 1.1×	62 0.3×	68 0.4×	98 0.6×	208 1.4×	45	547
Raphaël Le Mao	151 0.4×	211 1.0×	109 0.6×	98 0.6×	75 0.5×	47	543

Countries citing papers authored by Fernando Scudiero

Since Specialization

Citations

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

Fields of papers citing papers by Fernando Scudiero

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fernando Scudiero

This figure shows the co-authorship network connecting the top 25 collaborators of Fernando Scudiero. A scholar is included among the top collaborators of Fernando Scudiero 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 Fernando Scudiero. Fernando Scudiero is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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