Francesca Bevilacqua

20 papers receiving 188 citations

Peers

Francesca Bevilacqua
Comparison fields: 5 of 49
  • Surgery 71
  • Genetics 46
  • Cardiology and Cardiovascular Medicine 45
  • Pulmonary and Respiratory Medicine 44
  • Cognitive Neuroscience 41
Replace Eiichiro Noda with:
Eiichiro Noda Japan
Nargis Ahmad United Kingdom
Rahul Bhardwaj United States
Esther Pastor Spain
J F Muir France
C. G. Irvin United States
Anan Salloum United States
Jamie Brown United States
Isabel Portero‐Sanchez Spain
Francesca Bevilacqua relative to Eiichiro Noda Japan Eiichiro Noda's profile →
Citations per field
00.5×10.7×
Eiichiro Noda · 1×
Citations per year

Countries citing papers authored by Francesca Bevilacqua

Since Specialization
Citations

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

Fields of papers citing papers by Francesca Bevilacqua

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Francesca Bevilacqua

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 3
3 8
4 9
5 5
6 4
7 5
8 8
9 6
10 2
11 6
12 9
13 15
14
Assessment of left ventricular performance during laparoscopy.
2
15
Dopamine infusion and fluid administration improve renal function during laparoscopic surgery.
3
16 21
17 10
18
Influence of pneumoperitoneum on left ventricular filling pressures and NT-proBNP levels.
2
19 51
20 9

About Francesca Bevilacqua

Francesca Bevilacqua is a scholar working on Cardiology and Cardiovascular Medicine, Surgery and Pulmonary and Respiratory Medicine, having authored 21 papers that have together received 193 indexed citations. Recurring topics across this work include Hemodynamic Monitoring and Therapy (6 papers), Congenital Heart Disease Studies (5 papers) and Cardiac, Anesthesia and Surgical Outcomes (4 papers). The work is most often cited by research in Anesthesiology and Pain Medicine (16 citations), Critical Care and Intensive Care Medicine (13 citations) and Cognitive Neuroscience (41 citations). Francesca Bevilacqua has collaborated with scholars based in Italy, Japan and United Kingdom. Frequent co-authors include Elisabetta Marana, Andrea Russo, Elisabetta Tabolacci, Diego Martinelli, Giovanni Neri, Mike Snape, Franco Cavaliere, Enrico Di Stasio, Riccardo Marana and Maria Antonietta Isgrò. Their work appears in journals such as Journal of General Virology, Applied Mathematical Modelling and International Journal of Cardiology.

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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