Roberto Grassi
Impact in
- Health Informatics top 1%
- Artificial Intelligence in Healthcare and Education
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- Radiomics and Machine Learning in Medical Imaging
- MRI in cancer diagnosis
- COVID-19 diagnosis using AI
Papers in
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- Radiomics and Machine Learning in Medical Imaging 16
- MRI in cancer diagnosis 5
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- Digital Radiography and Breast Imaging 5
- Co-authors
- Vittorio Miele (16 shared papers)Vincenza Granata (30 shared papers)Roberta Fusco (28 shared papers)Emanuele Neri (6 shared papers)Roberta Grassi (19 shared papers)Francesca Coppola (4 shared papers)Antonella Petrillo (16 shared papers)Francesco Izzo (15 shared papers)
- Journals
- La radiologia medica (7 papers)Journal of Personalized Medicine (7 papers)Cancers (6 papers)Frontiers in Oncology (3 papers)Insights into Imaging (3 papers)
- Partner nations
- ItalyUnited StatesGermany
In The Last Decade
Roberto Grassi
54 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 108
- Health Informatics 136
- Radiology, Nuclear Medicine and Imaging 683
- Hepatology 118
- Oncology 359
- Critical Care and Intensive Care Medicine 41
Countries citing papers authored by Roberto Grassi
This map shows the geographic impact of Roberto Grassi'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 Grassi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Roberto Grassi more than expected).
Fields of papers citing papers by Roberto Grassi
This network shows the impact of papers produced by Roberto Grassi. 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 Grassi. The network helps show where Roberto Grassi may publish in the future.
Co-authors
The 25 scholars most cited alongside Roberto Grassi, 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 55 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 140 | |
| 2 | 2020 | 118 | |
| 3 | 2020 | 99 | |
| 4 | 2021 | 80 | |
| 5 | 2021 | 76 | |
| 6 | 2022 | 62 | |
| 7 | 2020 | 59 | |
| 8 | 2021 | 47 | |
| 9 | 2022 | 46 | |
| 10 | 2021 | 45 | |
| 11 | 2020 | 44 | |
| 12 | 2021 | 41 | |
| 13 | 2020 | 39 | |
| 14 | 2021 | 39 | |
| 15 | 2021 | 38 | |
| 16 | 2021 | 38 | |
| 17 | 2023 | 36 | |
| 18 | 2020 | 36 | |
| 19 | 2016 | 35 | |
| 20 | 2020 | 30 |
About Roberto Grassi
Roberto Grassi is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Oncology, Biomedical Engineering and Surgery, having authored 55 papers that have together received 1.6k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (16 papers), AI in cancer detection (6 papers), MRI in cancer diagnosis (5 papers), Digital Radiography and Breast Imaging (5 papers), Colorectal Cancer Surgical Treatments (4 papers), Advanced X-ray and CT Imaging (4 papers), Cutaneous Melanoma Detection and Management (3 papers) and Cholangiocarcinoma and Gallbladder Cancer Studies (3 papers). The work is most often cited by research in Health Informatics (136 citations), Radiology, Nuclear Medicine and Imaging (683 citations), Hepatology (118 citations), Oncology (359 citations) and Critical Care and Intensive Care Medicine (41 citations). Roberto Grassi has collaborated with scholars based in Italy, United States and Germany. Frequent co-authors include Vittorio Miele, Vincenza Granata, Roberta Fusco, Emanuele Neri, Roberta Grassi, Francesca Coppola, Antonella Petrillo, Francesco Izzo, Alfonso Reginelli and Salvatore Cappabianca. Their work appears in journals such as La radiologia medica, Journal of Personalized Medicine, Cancers, Frontiers in Oncology and Insights into Imaging.
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.