Matteo Pepa
- Radiology, Nuclear Medicine and Imaging top 10%
- Pulmonary and Respiratory Medicine
- Biomedical Engineering
- Radiation top 10%
- Computer Vision and Pattern Recognition
- Co-authors
- Barbara Alicja Jereczek‐FossaGiulia MarvasoLars Johannes IsakssonRoberto OrecchiaMattia ZaffaroniStefania VolpeGiulia CorraoDaniela Alterio
- Topics
- Advanced Radiotherapy Techniques (13 papers)Prostate Cancer Diagnosis and Treatment (7 papers)Radiomics and Machine Learning in Medical Imaging (6 papers)
- Journals
- International Journal of Molecular SciencesInternational Journal of Radiation Oncology*Biology*PhysicsSensors
- Partner nations
- ItalyPolandUnited Kingdom
In The Last Decade
Matteo Pepa
30 papers receiving 327 citations
Peers
Comparison fields: 5 of 79
- Radiology, Nuclear Medicine and Imaging 155
- Pulmonary and Respiratory Medicine 109
- Biomedical Engineering 75
- Radiation 73
- Computer Vision and Pattern Recognition 46
Countries citing papers authored by Matteo Pepa
This map shows the geographic impact of Matteo Pepa'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 Matteo Pepa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matteo Pepa more than expected).
Fields of papers citing papers by Matteo Pepa
This network shows the impact of papers produced by Matteo Pepa. 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 Matteo Pepa. The network helps show where Matteo Pepa may publish in the future.
Co-authorship network of co-authors of Matteo Pepa
This figure shows the co-authorship network connecting the top 25 collaborators of Matteo Pepa. A scholar is included among the top collaborators of Matteo Pepa 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 Matteo Pepa. Matteo Pepa 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 | 3 | |
| 3 | 0 | |
| 4 | 6 | |
| 5 | 5 | |
| 6 | 2 | |
| 7 | 7 | |
| 8 | 4 | |
| 9 | 5 | |
| 10 | 18 | |
| 11 | 14 | |
| 12 | 2 | |
| 13 | 5 | |
| 14 | 12 | |
| 15 | 72 | |
| 16 | 14 | |
| 17 | 1 | |
| 18 | 3 | |
| 19 | 50 | |
| 20 | 52 |
About Matteo Pepa
Matteo Pepa is a scholar working on Radiation, Pulmonary and Respiratory Medicine and Radiology, Nuclear Medicine and Imaging, having authored 33 papers that have together received 332 indexed citations. Recurring topics across this work include Advanced Radiotherapy Techniques (13 papers), Prostate Cancer Diagnosis and Treatment (7 papers) and Radiomics and Machine Learning in Medical Imaging (6 papers). The work is most often cited by research in Health Informatics (19 citations), Radiation (73 citations) and Radiology, Nuclear Medicine and Imaging (155 citations). Matteo Pepa has collaborated with scholars based in Italy, Poland and United Kingdom. Frequent co-authors include Barbara Alicja Jereczek‐Fossa, Giulia Marvaso, Lars Johannes Isaksson, Roberto Orecchia, Mattia Zaffaroni, Stefania Volpe, Giulia Corrao, Daniela Alterio, Matteo Augugliaro and Maria Cristina Leonardi. Their work appears in journals such as International Journal of Molecular Sciences, International Journal of Radiation Oncology*Biology*Physics and Sensors.
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.