Serena Salzano

647 citations
27 papers · 502 indexed · h-index 13
Topics
Radiomics and Machine Learning in Medical Imaging (4 papers)Artificial Intelligence in Healthcare and Education (3 papers)Cell Adhesion Molecules Research (3 papers)

In The Last Decade

Serena Salzano

23 papers receiving 491 citations

Peers

Serena Salzano
Comparison fields: 5 of 99
  • Molecular Biology 128
  • Plant Science 112
  • Biomedical Engineering 98
  • Cancer Research 83
  • Surgery 71
Replace Kazuo Sanada with:
Kazuo Sanada Japan
Satoshi Watanabe Japan
Marlène Gallet France
N. P. Piesco United States
L. Knott United Kingdom
Hiroki Nagayasu Japan
Isabelle Barbosa France
Nilana M.T. Barros Brazil
Jorge Escobar‐Vera Chile
Serena Salzano relative to Kazuo Sanada Japan Kazuo Sanada's profile →
Citations per field
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Citations per year

Countries citing papers authored by Serena Salzano

Since Specialization
Citations

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

Fields of papers citing papers by Serena Salzano

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Serena Salzano

This figure shows the co-authorship network connecting the top 25 collaborators of Serena Salzano. A scholar is included among the top collaborators of Serena Salzano 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 Serena Salzano. Serena Salzano 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 1
2 1
3 2
4 0
5 1
6 1
7 0
8 4
9 0
10 1
11 20
12 17
13 127
14 35
15 10
16 13
17
17 beta-Estradiol overcomes a G1 block induced by HMG-CoA reductase inhibitors and fosters cell cycle progression without inducing ERK-1 and -2 MAP kinases activation.
50
18 29
19 20
20 24

About Serena Salzano

Serena Salzano is a scholar working on Health Informatics, Immunology and Allergy and Cancer Research, having authored 27 papers that have together received 502 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (4 papers), Artificial Intelligence in Healthcare and Education (3 papers) and Cell Adhesion Molecules Research (3 papers). The work is most often cited by research in Health Informatics (12 citations), Immunology and Allergy (38 citations) and Cancer Research (83 citations). Serena Salzano has collaborated with scholars based in Italy, Greece and United Kingdom. Frequent co-authors include Antonietta Santoro, Rocchina Barbieri, Matilde Valeria Ursini, Maria Brigida Lioi, Giacomo Rossi, Loredana Postiglione, Ludovico Sbordone, Luca Ramaglia, Stefania Montagnani and Mario Vitale. Their work appears in journals such as Gastroenterology, The Journal of Clinical Endocrinology & Metabolism and Biochemical and Biophysical Research Communications.

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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