Massimo Calabrese

4.1k citations
106 papers · 2.4k · h-index 26

Impact in

Papers in

Massimo Calabrese

104 papers receiving 2.3k citations

Peers

Massimo Calabrese
Comparison fields: 5 of 113
  • Radiology, Nuclear Medicine and Imaging 1.2k
  • Pathology and Forensic Medicine 527
  • Pulmonary and Respiratory Medicine 907
  • Cancer Research 402
  • Artificial Intelligence 846
Replace Eileen Rakovitch with:
Eileen Rakovitch Canada
Elizabeth O’Flynn United Kingdom
Naoyuki Shigematsu Japan
Barbara M. Klinkhammer Germany
Kumar Sandrasegaran United States
Daniele La Forgia Italy
Isabelle Leconte Belgium
Norman L. Sadowsky United States
Isabel Amendoeira Portugal
Christian D. Fankhauser Switzerland
Massimo Calabrese relative to Eileen Rakovitch Canada Eileen Rakovitch's profile →
Citations per field
00.5×5.8×
Eileen Rakovitch · 1×
Citations per year

Countries citing papers authored by Massimo Calabrese

Since Specialization
Citations

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

Fields of papers citing papers by Massimo Calabrese

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Massimo Calabrese, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Massimo Calabrese Line = papers co-authored together Massimo Calabrese links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 106 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018193
2 2016163
3 2001126
4 2012103
5 2016100
6 201882
7 201181
8 200868
9 201166
10 201465
11 201161
12 201951
13 201848
14 201245
15 201945
16 201043
17 201341
18 199835
19 202234
20 201634

About Massimo Calabrese

Massimo Calabrese is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Artificial Intelligence, Pathology and Forensic Medicine and Cancer Research, having authored 106 papers that have together received 2.4k indexed citations. Recurring topics across this work include Digital Radiography and Breast Imaging (28 papers), AI in cancer detection (28 papers), Breast Lesions and Carcinomas (24 papers), Breast Cancer Treatment Studies (23 papers), MRI in cancer diagnosis (20 papers), Radiomics and Machine Learning in Medical Imaging (19 papers), Medical Imaging Techniques and Applications (16 papers) and Advanced MRI Techniques and Applications (12 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (1.2k citations), Pathology and Forensic Medicine (527 citations), Pulmonary and Respiratory Medicine (907 citations), Cancer Research (402 citations) and Artificial Intelligence (846 citations). Massimo Calabrese has collaborated with scholars based in Italy, United Kingdom and Australia. Frequent co-authors include Alberto Tagliafico, Nehmat Houssami, Francesca Valdora, Federica Rossi, Bianca Bignotti, Francesco Monetti, Alessio Signori, Carlo Martinoli, Giovanna Mariscotti and Giulio Tagliafico. Their work appears in journals such as European Radiology, La radiologia medica, British Journal of Radiology, The Breast and Acta Radiologica.

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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