Roberto Gatta
Impact in
- Health Informatics top 5%
-
- Radiomics and Machine Learning in Medical Imaging
- Medical Imaging Techniques and Applications
Papers in
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- Radiomics and Machine Learning in Medical Imaging 31
- Medical Imaging Techniques and Applications 8
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- Sarcoma Diagnosis and Treatment 5
- Co-authors
- Vincenzo Valentini (27 shared papers)Andrea Damiani (22 shared papers)N. Dinapoli (18 shared papers)Luca Boldrini (20 shared papers)Jacopo Lenkowicz (11 shared papers)Mauro Vallati (16 shared papers)Carlotta Masciocchi (13 shared papers)Calogero Casà (9 shared papers)
- Journals
- La radiologia medica (5 papers)Cancers (4 papers)Journal of Clinical Medicine (4 papers)International Journal of Radiation Oncology*Biology*Physics (3 papers)Journal of Hypertension (3 papers)
- Partner nations
- ItalySwitzerlandUnited Kingdom
In The Last Decade
Roberto Gatta
74 papers receiving 970 citations
Peers
Comparison fields: 5 of 106
- Health Informatics 28
- Radiology, Nuclear Medicine and Imaging 343
- Management Information Systems 77
- Oncology 152
- Health Information Management 20
Countries citing papers authored by Roberto Gatta
This map shows the geographic impact of Roberto Gatta'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 Roberto Gatta with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Roberto Gatta more than expected).
Fields of papers citing papers by Roberto Gatta
This network shows the impact of papers produced by Roberto Gatta. 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 Roberto Gatta. The network helps show where Roberto Gatta may publish in the future.
Co-authors
The 25 scholars most cited alongside Roberto Gatta, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 85 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 102 | |
| 2 | 2020 | 77 | |
| 3 | 2020 | 55 | |
| 4 | 2015 | 49 | |
| 5 | 2020 | 39 | |
| 6 | 2020 | 38 | |
| 7 | 2018 | 34 | |
| 8 | 2019 | 30 | |
| 9 | 2016 | 30 | |
| 10 | 2018 | 29 | |
| 11 | 2015 | 27 | |
| 12 | 2021 | 25 | |
| 13 | 2019 | 20 | |
| 14 | 2017 | 19 | |
| 15 | 2008 | 19 | |
| 16 | 2014 | 17 | |
| 17 | 2020 | 16 | |
| 18 | 2021 | 16 | |
| 19 | 2018 | 15 | |
| 20 | 2022 | 14 |
About Roberto Gatta
Roberto Gatta is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Artificial Intelligence, Oncology and Surgery, having authored 85 papers that have together received 973 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (31 papers), Business Process Modeling and Analysis (8 papers), Medical Imaging Techniques and Applications (8 papers), Colorectal Cancer Screening and Detection (6 papers), Blood Pressure and Hypertension Studies (5 papers), Semantic Web and Ontologies (5 papers), Colorectal Cancer Surgical Treatments (5 papers) and Sarcoma Diagnosis and Treatment (5 papers). The work is most often cited by research in Health Informatics (28 citations), Radiology, Nuclear Medicine and Imaging (343 citations), Management Information Systems (77 citations), Oncology (152 citations) and Health Information Management (20 citations). Roberto Gatta has collaborated with scholars based in Italy, Switzerland and United Kingdom. Frequent co-authors include Vincenzo Valentini, Andrea Damiani, N. Dinapoli, Luca Boldrini, Jacopo Lenkowicz, Mauro Vallati, Carlotta Masciocchi, Calogero Casà, Johan van Soest and Davide Cusumano. Their work appears in journals such as La radiologia medica, Cancers, Journal of Clinical Medicine, International Journal of Radiation Oncology*Biology*Physics and Journal of Hypertension.
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.