Pasquale Tamborra

938 citations
29 papers · 682 indexed · h-index 16
Topics
Radiomics and Machine Learning in Medical Imaging (18 papers)AI in cancer detection (14 papers)Breast Cancer Treatment Studies (8 papers)
Partner nations
Italy

In The Last Decade

Pasquale Tamborra

28 papers receiving 674 citations

Peers

Pasquale Tamborra
Comparison fields: 5 of 68
  • Radiology, Nuclear Medicine and Imaging 486
  • Artificial Intelligence 392
  • Cancer Research 124
  • Pulmonary and Respiratory Medicine 120
  • Biomedical Engineering 102
Replace Vittorio Didonna with:
Vittorio Didonna Italy
Lan Li China
Lakshmanan Sannachi Canada
Alexandra Edwards United States
Zixiao Lu China
F. W. Samuelson United States
Neha Bhooshan United States
Belinda Curpen Canada
Zeyan Xu China
Yiwen Xu United States
Pasquale Tamborra relative to Vittorio Didonna Italy Vittorio Didonna's profile →
Citations per field
00.5×1.5×
Vittorio Didonna · 1×
Citations per year

Countries citing papers authored by Pasquale Tamborra

Since Specialization
Citations

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

Fields of papers citing papers by Pasquale Tamborra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pasquale Tamborra

This figure shows the co-authorship network connecting the top 25 collaborators of Pasquale Tamborra. A scholar is included among the top collaborators of Pasquale Tamborra 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 Pasquale Tamborra. Pasquale Tamborra 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 8
2 5
3 5
4 11
5 6
6 30
7 36
8 28
9 54
10 34
11 6
12 42
13 76
14 43
15 37
16 40
17 8
18 24
19 12
20 0

About Pasquale Tamborra

Pasquale Tamborra is a scholar working on Radiology, Nuclear Medicine and Imaging, Cancer Research and Artificial Intelligence, having authored 29 papers that have together received 682 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (18 papers), AI in cancer detection (14 papers) and Breast Cancer Treatment Studies (8 papers). The work is most often cited by research in Health Informatics (29 citations), Radiology, Nuclear Medicine and Imaging (486 citations) and Artificial Intelligence (392 citations). Pasquale Tamborra has collaborated with scholars based in Italy. Frequent co-authors include Raffaella Massafra, Annarita Fanizzi, Vittorio Didonna, Daniele La Forgia, R. Bellotti, Sabina Tangaro, Vito Lorusso, Alfredo Zito, Agnese Latorre and Samantha Bove. Their work appears in journals such as PLoS ONE, Scientific Reports and BMC Bioinformatics.

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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