Roberto Grassi
- Radiology, Nuclear Medicine and Imaging top 2%
- Oncology top 10%
- Pulmonary and Respiratory Medicine top 10%
- Surgery top 10%
- Biomedical Engineering top 10%
- Co-authors
- Vittorio MieleVincenza GranataRoberta FuscoEmanuele NeriRoberta GrassiFrancesca CoppolaAntonella PetrilloFrancesco Izzo
- Topics
- Radiomics and Machine Learning in Medical Imaging (21 papers)AI in cancer detection (11 papers)COVID-19 diagnosis using AI (7 papers)
- Journals
- SHILAP Revista de lepidopterologíaScientific ReportsInternational Journal of Environmental Research and Public Health
- Partner nations
- ItalyUnited StatesGermany
In The Last Decade
Roberto Grassi
53 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 106
- Radiology, Nuclear Medicine and Imaging 872
- Oncology 441
- Pulmonary and Respiratory Medicine 342
- Surgery 338
- Biomedical Engineering 269
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-authorship network of co-authors of Roberto Grassi
This figure shows the co-authorship network connecting the top 25 collaborators of Roberto Grassi. A scholar is included among the top collaborators of Roberto Grassi 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 Roberto Grassi. Roberto Grassi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 5 | |
| 4 | 11 | |
| 5 | 28 | |
| 6 | 56 | |
| 7 | 9 | |
| 8 | 15 | |
| 9 | 21 | |
| 10 | 21 | |
| 11 | 35 | |
| 12 | 11 | |
| 13 | 10 | |
| 14 | 12 | |
| 15 | 8 | |
| 16 | 11 | |
| 17 | 35 | |
| 18 | 136 | |
| 19 | 58 | |
| 20 | 17 |
About Roberto Grassi
Roberto Grassi is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Critical Care and Intensive Care Medicine, having authored 55 papers that have together received 1.5k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (21 papers), AI in cancer detection (11 papers) and COVID-19 diagnosis using AI (7 papers). The work is most often cited by research in Health Informatics (153 citations), Radiology, Nuclear Medicine and Imaging (872 citations) and Hepatology (165 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, Salvatore Cappabianca and Alfonso Reginelli. Their work appears in journals such as SHILAP Revista de lepidopterología, Scientific Reports and International Journal of Environmental Research and Public Health.
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.