Emma D’Ippolito
- Radiology, Nuclear Medicine and Imaging top 10%
- Pulmonary and Respiratory Medicine
- Oncology
- Surgery
- Biomedical Engineering
- Co-authors
- Valerio NardoneAlfonso ReginelliSalvatore CappabiancaIsacco DesideriRoberta GrassiSalvatore AnnunziataLuca BoldriniAlessandra Farchione
- Topics
- Radiomics and Machine Learning in Medical Imaging (4 papers)Brain Metastases and Treatment (4 papers)Radiation Therapy and Dosimetry (4 papers)
- Journals
- SHILAP Revista de lepidopterologíaRadiotherapy and OncologyCancers
- Partner nations
- ItalyUnited StatesSwitzerland
In The Last Decade
Emma D’Ippolito
19 papers receiving 338 citations
Peers
Comparison fields: 5 of 55
- Radiology, Nuclear Medicine and Imaging 197
- Pulmonary and Respiratory Medicine 123
- Oncology 97
- Surgery 73
- Biomedical Engineering 66
Countries citing papers authored by Emma D’Ippolito
This map shows the geographic impact of Emma D’Ippolito'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 Emma D’Ippolito with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Emma D’Ippolito more than expected).
Fields of papers citing papers by Emma D’Ippolito
This network shows the impact of papers produced by Emma D’Ippolito. 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 Emma D’Ippolito. The network helps show where Emma D’Ippolito may publish in the future.
Co-authorship network of co-authors of Emma D’Ippolito
This figure shows the co-authorship network connecting the top 25 collaborators of Emma D’Ippolito. A scholar is included among the top collaborators of Emma D’Ippolito 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 Emma D’Ippolito. Emma D’Ippolito 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 | 6 | |
| 5 | 17 | |
| 6 | 5 | |
| 7 | 6 | |
| 8 | 8 | |
| 9 | 142 | |
| 10 | 37 | |
| 11 | 13 | |
| 12 | 32 | |
| 13 | 9 | |
| 14 | 12 | |
| 15 | 10 | |
| 16 | 20 | |
| 17 | 7 | |
| 18 | 11 | |
| 19 | 1 | |
| 20 | 0 |
About Emma D’Ippolito
Emma D’Ippolito is a scholar working on Radiology, Nuclear Medicine and Imaging, Radiation and Pulmonary and Respiratory Medicine, having authored 23 papers that have together received 341 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (4 papers), Brain Metastases and Treatment (4 papers) and Radiation Therapy and Dosimetry (4 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (197 citations), Otorhinolaryngology (35 citations) and Radiation (48 citations). Emma D’Ippolito has collaborated with scholars based in Italy, United States and Switzerland. Frequent co-authors include Valerio Nardone, Alfonso Reginelli, Salvatore Cappabianca, Isacco Desideri, Roberta Grassi, Salvatore Annunziata, Luca Boldrini, Alessandra Farchione, Maria Paola Belfiore and Giovanna Vacca. Their work appears in journals such as SHILAP Revista de lepidopterología, Radiotherapy and Oncology and Cancers.
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.