Gabriele Campanella
- Artificial Intelligence top 1%
- Radiology, Nuclear Medicine and Imaging top 1%
- Oncology top 5%
- Molecular Biology top 10%
- Immunology top 5%
- Co-authors
- Andrew D. LusterThomas J. FuchsRichard A. ColvinVitor Werneck Krauss SilvaEdi BrogiLuke GeneslawKlaus J. BusamMatthew G. Hanna
- Topics
- Chemokine receptors and signaling (9 papers)AI in cancer detection (6 papers)Immunotherapy and Immune Responses (6 papers)
- Journals
- Proceedings of the National Academy of SciencesJournal of Biological ChemistryJournal of Clinical Investigation
- Partner nations
- United StatesItalyFrance
In The Last Decade
Gabriele Campanella
30 papers receiving 3.9k citations
Hit Papers
Peers
Comparison fields: 5 of 143
- Artificial Intelligence 1.2k
- Radiology, Nuclear Medicine and Imaging 1.0k
- Oncology 912
- Molecular Biology 856
- Immunology 818
Countries citing papers authored by Gabriele Campanella
This map shows the geographic impact of Gabriele Campanella'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 Gabriele Campanella with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gabriele Campanella more than expected).
Fields of papers citing papers by Gabriele Campanella
This network shows the impact of papers produced by Gabriele Campanella. 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 Gabriele Campanella. The network helps show where Gabriele Campanella may publish in the future.
Co-authorship network of co-authors of Gabriele Campanella
This figure shows the co-authorship network connecting the top 25 collaborators of Gabriele Campanella. A scholar is included among the top collaborators of Gabriele Campanella 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 Gabriele Campanella. Gabriele Campanella is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 16 | |
| 2 | 15 | |
| 3 | 10 | |
| 4 | 37 | |
| 5 | 1 | |
| 6 | Beyond Classification: Whole Slide Tissue Histopathology Analysis By End-To-End Part Learning | 9 |
| 7 | DeepPET: A deep encoder–decoder network for directly solving the PET image reconstruction inverse problembreakdown → | 201 |
| 8 | 34 | |
| 9 | 129 | |
| 10 | 88 | |
| 11 | 5 | |
| 12 | The lysophosphatidic acid receptor LPA1 links pulmonary fibrosis to lung injury by mediating fibroblast recruitment and vascular leakbreakdown → | 626 |
| 13 | 81 | |
| 14 | 80 | |
| 15 | 58 | |
| 16 | 35 | |
| 17 | 57 | |
| 18 | 219 | |
| 19 | 164 | |
| 20 | 78 |
About Gabriele Campanella
Gabriele Campanella is a scholar working on Immunology and Allergy, Immunology and Virology, having authored 31 papers that have together received 3.9k indexed citations. Recurring topics across this work include Chemokine receptors and signaling (9 papers), AI in cancer detection (6 papers) and Immunotherapy and Immune Responses (6 papers). The work is most often cited by research in Health Informatics (132 citations), Radiology, Nuclear Medicine and Imaging (1.0k citations) and Immunology (818 citations). Gabriele Campanella has collaborated with scholars based in United States, Italy and France. Frequent co-authors include Andrew D. Luster, Thomas J. Fuchs, Richard A. Colvin, Vitor Werneck Krauss Silva, Edi Brogi, Luke Geneslaw, Klaus J. Busam, Matthew G. Hanna, Victor E. Reuter and David S. Klimstra. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Journal of Clinical Investigation.
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.