Matea Pavic
Impact in
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- Radiomics and Machine Learning in Medical Imaging
- Medical Imaging Techniques and Applications
- Radiation top 5%
- Advanced Radiotherapy Techniques
Papers in
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- Radiomics and Machine Learning in Medical Imaging 8
- Medical Imaging Techniques and Applications 2
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- Advanced Radiotherapy Techniques 6
- Co-authors
- Matthias Gückenberger (20 shared papers)Stephanie Tanadini‐Lang (15 shared papers)Marta Bogowicz (11 shared papers)Martin W. Huellner (6 shared papers)Diem Vuong (7 shared papers)Johannes Kraft (3 shared papers)Gerhard Tröster (3 shared papers)Vanessa Klaas (3 shared papers)
- Journals
- Radiation Oncology (5 papers)Frontiers in Oncology (3 papers)Strahlentherapie und Onkologie (2 papers)Physics and Imaging in Radiation Oncology (2 papers)Journal of Clinical Oncology (1 paper)
- Partner nations
- SwitzerlandGermanyItaly
In The Last Decade
Matea Pavic
29 papers receiving 665 citations
Peers
Comparison fields: 5 of 65
- Radiology, Nuclear Medicine and Imaging 304
- Radiation 93
- Health Informatics 12
- Otorhinolaryngology 35
- Oncology 140
Countries citing papers authored by Matea Pavic
This map shows the geographic impact of Matea Pavic'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 Matea Pavic with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matea Pavic more than expected).
Fields of papers citing papers by Matea Pavic
This network shows the impact of papers produced by Matea Pavic. 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 Matea Pavic. The network helps show where Matea Pavic may publish in the future.
Co-authors
The 25 scholars most cited alongside Matea Pavic, 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 31 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 156 | |
| 2 | 2020 | 72 | |
| 3 | 2019 | 53 | |
| 4 | 2019 | 50 | |
| 5 | 2019 | 50 | |
| 6 | 2020 | 43 | |
| 7 | 2021 | 36 | |
| 8 | 2020 | 32 | |
| 9 | 2020 | 30 | |
| 10 | 2021 | 24 | |
| 11 | 2021 | 16 | |
| 12 | 2021 | 14 | |
| 13 | 2021 | 13 | |
| 14 | 2022 | 13 | |
| 15 | 2021 | 11 | |
| 16 | 2020 | 9 | |
| 17 | 2022 | 6 | |
| 18 | 2020 | 6 | |
| 19 | 2021 | 6 | |
| 20 | 2014 | 6 |
About Matea Pavic
Matea Pavic is a scholar working on Radiology, Nuclear Medicine and Imaging, Radiation, Oncology, Surgery and Pulmonary and Respiratory Medicine, having authored 31 papers that have together received 667 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (8 papers), Advanced Radiotherapy Techniques (6 papers), Health Systems, Economic Evaluations, Quality of Life (3 papers), Pancreatic and Hepatic Oncology Research (3 papers), Cancer Genomics and Diagnostics (2 papers), Radiation Therapy and Dosimetry (2 papers), Medical Imaging Techniques and Applications (2 papers) and Pharmaceutical Economics and Policy (2 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (304 citations), Radiation (93 citations), Health Informatics (12 citations), Otorhinolaryngology (35 citations) and Oncology (140 citations). Matea Pavic has collaborated with scholars based in Switzerland, Germany and Italy. Frequent co-authors include Matthias Gückenberger, Stephanie Tanadini‐Lang, Marta Bogowicz, Martin W. Huellner, Diem Vuong, Johannes Kraft, Gerhard Tröster, Vanessa Klaas, Nicolaus Andratschke and Gudrun Theile. Their work appears in journals such as Radiation Oncology, Frontiers in Oncology, Strahlentherapie und Onkologie, Physics and Imaging in Radiation Oncology and Journal of Clinical Oncology.
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.