Giulia Buizza
Impact in
- Radiation top 5%
- Advanced Radiotherapy Techniques
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- Radiomics and Machine Learning in Medical Imaging
- Medical Imaging Techniques and Applications
- Advanced MRI Techniques and Applications
- MRI in cancer diagnosis
Papers in
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- MRI in cancer diagnosis 9
- Medical Imaging Techniques and Applications 6
- Radiomics and Machine Learning in Medical Imaging 6
- Advanced Neuroimaging Techniques and Applications 5
- Advanced MRI Techniques and Applications 4
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- Lung Cancer Diagnosis and Treatment 3
- Co-authors
- Chiara Paganelli (18 shared papers)G. Baroni (17 shared papers)Marco Riboldi (4 shared papers)Iuliana Toma-Daşu (2 shared papers)Paul Keall (2 shared papers)Örjan Smedby (2 shared papers)Michael Reiner (1 shared paper)Lorenzo Preda (9 shared papers)
In The Last Decade
Giulia Buizza
21 papers receiving 345 citations
Peers
Comparison fields: 5 of 45
- Radiation 151
- Radiology, Nuclear Medicine and Imaging 285
- Health Informatics 14
- Pulmonary and Respiratory Medicine 150
- Genetics 25
Countries citing papers authored by Giulia Buizza
This map shows the geographic impact of Giulia Buizza'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 Giulia Buizza with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Giulia Buizza more than expected).
Fields of papers citing papers by Giulia Buizza
This network shows the impact of papers produced by Giulia Buizza. 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 Giulia Buizza. The network helps show where Giulia Buizza may publish in the future.
Co-authors
The 25 scholars most cited alongside Giulia Buizza, 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 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 106 | |
| 2 | 2019 | 41 | |
| 3 | 2018 | 40 | |
| 4 | 2021 | 37 | |
| 5 | 2019 | 25 | |
| 6 | 2020 | 16 | |
| 7 | 2019 | 12 | |
| 8 | 2019 | 11 | |
| 9 | 2020 | 10 | |
| 10 | 2020 | 8 | |
| 11 | 2021 | 7 | |
| 12 | 2023 | 6 | |
| 13 | 2024 | 6 | |
| 14 | 2023 | 5 | |
| 15 | 2021 | 4 | |
| 16 | 2023 | 3 | |
| 17 | 2020 | 3 | |
| 18 | 2021 | 2 | |
| 19 | 2022 | 1 | |
| 20 | 2019 | 1 |
About Giulia Buizza
Giulia Buizza is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Radiation, Genetics and Rheumatology, having authored 21 papers that have together received 345 indexed citations. Recurring topics across this work include MRI in cancer diagnosis (9 papers), Medical Imaging Techniques and Applications (6 papers), Radiomics and Machine Learning in Medical Imaging (6 papers), Advanced Neuroimaging Techniques and Applications (5 papers), Advanced MRI Techniques and Applications (4 papers), Lung Cancer Diagnosis and Treatment (3 papers), Advanced Radiotherapy Techniques (3 papers) and Bone Tumor Diagnosis and Treatments (3 papers). The work is most often cited by research in Radiation (151 citations), Radiology, Nuclear Medicine and Imaging (285 citations), Health Informatics (14 citations), Pulmonary and Respiratory Medicine (150 citations) and Genetics (25 citations). Giulia Buizza has collaborated with scholars based in Italy, Germany and Australia. Frequent co-authors include Chiara Paganelli, G. Baroni, Marco Riboldi, Iuliana Toma-Daşu, Paul Keall, Örjan Smedby, Michael Reiner, Lorenzo Preda, Florian Kamp and Christopher Kurz. Their work appears in journals such as Physica Medica, Medical Physics, Neuroradiology, 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.