Raffaella Massafra
- Radiology, Nuclear Medicine and Imaging top 2%
- Artificial Intelligence top 2%
- Pulmonary and Respiratory Medicine top 10%
- Oncology top 10%
- Cancer Research top 10%
- Co-authors
- Annarita FanizziDaniele La ForgiaVittorio DidonnaPasquale TamborraR. BellottiSabina TangaroVito LorussoSamantha Bove
- Topics
- Radiomics and Machine Learning in Medical Imaging (36 papers)AI in cancer detection (29 papers)MRI in cancer diagnosis (11 papers)
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEScientific Reports
- Partner nations
- ItalyTürkiyeUnited States
In The Last Decade
Raffaella Massafra
85 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 103
- Radiology, Nuclear Medicine and Imaging 708
- Artificial Intelligence 542
- Pulmonary and Respiratory Medicine 304
- Oncology 242
- Cancer Research 189
Countries citing papers authored by Raffaella Massafra
This map shows the geographic impact of Raffaella Massafra'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 Raffaella Massafra with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Raffaella Massafra more than expected).
Fields of papers citing papers by Raffaella Massafra
This network shows the impact of papers produced by Raffaella Massafra. 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 Raffaella Massafra. The network helps show where Raffaella Massafra may publish in the future.
Co-authorship network of co-authors of Raffaella Massafra
This figure shows the co-authorship network connecting the top 25 collaborators of Raffaella Massafra. A scholar is included among the top collaborators of Raffaella Massafra 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 Raffaella Massafra. Raffaella Massafra 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 | 0 | |
| 3 | 1 | |
| 4 | 8 | |
| 5 | 1 | |
| 6 | 2 | |
| 7 | 3 | |
| 8 | 2 | |
| 9 | 0 | |
| 10 | 3 | |
| 11 | 1 | |
| 12 | 1 | |
| 13 | 0 | |
| 14 | 5 | |
| 15 | 5 | |
| 16 | 8 | |
| 17 | 2 | |
| 18 | 4 | |
| 19 | 35 | |
| 20 | 36 |
About Raffaella Massafra
Raffaella Massafra is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Oncology, having authored 95 papers that have together received 1.3k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (36 papers), AI in cancer detection (29 papers) and MRI in cancer diagnosis (11 papers). The work is most often cited by research in Health Informatics (42 citations), Radiology, Nuclear Medicine and Imaging (708 citations) and Artificial Intelligence (542 citations). Raffaella Massafra has collaborated with scholars based in Italy, Türkiye and United States. Frequent co-authors include Annarita Fanizzi, Daniele La Forgia, Vittorio Didonna, Pasquale Tamborra, R. Bellotti, Sabina Tangaro, Vito Lorusso, Samantha Bove, Maria Colomba Comes and Alfredo Zito. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.
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.