Giovanni Valbusa
Impact in
- Health Informatics top 10%
-
- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
- Monoclonal and Polyclonal Antibodies Research
Papers in
-
- Radiomics and Machine Learning in Medical Imaging 4
- Advanced MRI Techniques and Applications 3
- COVID-19 diagnosis using AI 2
- MRI in cancer diagnosis 2
- Genetics 2
- Glioma Diagnosis and Treatment 2
- Co-authors
- Paolo Oliva (3 shared papers)Alexander Berndt (3 shared papers)Raffaella Giavazzi (3 shared papers)Sonia Colombo Serra (4 shared papers)Enzo Grossi (5 shared papers)Massimo Buscema (2 shared papers)Maurizio D’Incalci (1 shared paper)Ezia Bello (1 shared paper)
- Journals
- Cancer Research (2 papers)JBIC Journal of Biological Inorganic Chemistry (1 paper)Annals of Biomedical Engineering (1 paper)Neuroradiology (1 paper)Medical Image Analysis (1 paper)
- Partner nations
- ItalyGermanyNetherlands
In The Last Decade
Giovanni Valbusa
20 papers receiving 541 citations
Peers
Comparison fields: 5 of 76
- Health Informatics 23
- Radiology, Nuclear Medicine and Imaging 165
- Oncology 81
- Cancer Research 37
- Molecular Biology 171
Countries citing papers authored by Giovanni Valbusa
This map shows the geographic impact of Giovanni Valbusa'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 Giovanni Valbusa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Giovanni Valbusa more than expected).
Fields of papers citing papers by Giovanni Valbusa
This network shows the impact of papers produced by Giovanni Valbusa. 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 Giovanni Valbusa. The network helps show where Giovanni Valbusa may publish in the future.
Co-authors
The 25 scholars most cited alongside Giovanni Valbusa, 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 | 2011 | 130 | |
| 2 | 2012 | 83 | |
| 3 | 2021 | 78 | |
| 4 | 2018 | 43 | |
| 5 | 2020 | 36 | |
| 6 | 2014 | 33 | |
| 7 | 2014 | 24 | |
| 8 | 2019 | 22 | |
| 9 | 2020 | 20 | |
| 10 | 2020 | 14 | |
| 11 | 2018 | 13 | |
| 12 | 2023 | 13 | |
| 13 | 2019 | 7 | |
| 14 | 2020 | 7 | |
| 15 | 2024 | 6 | |
| 16 | 2024 | 6 | |
| 17 | 2021 | 5 | |
| 18 | 2018 | 4 | |
| 19 | 2019 | 3 | |
| 20 | 2021 | 3 |
About Giovanni Valbusa
Giovanni Valbusa is a scholar working on Radiology, Nuclear Medicine and Imaging, Genetics, Health Informatics, Cellular and Molecular Neuroscience and Cardiology and Cardiovascular Medicine, having authored 21 papers that have together received 550 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (4 papers), Lanthanide and Transition Metal Complexes (3 papers), Advanced MRI Techniques and Applications (3 papers), Angiogenesis and VEGF in Cancer (3 papers), Cardiovascular Function and Risk Factors (2 papers), COVID-19 diagnosis using AI (2 papers), Glioma Diagnosis and Treatment (2 papers) and MRI in cancer diagnosis (2 papers). The work is most often cited by research in Health Informatics (23 citations), Radiology, Nuclear Medicine and Imaging (165 citations), Oncology (81 citations), Cancer Research (37 citations) and Molecular Biology (171 citations). Giovanni Valbusa has collaborated with scholars based in Italy, Germany and Netherlands. Frequent co-authors include Paolo Oliva, Alexander Berndt, Raffaella Giavazzi, Sonia Colombo Serra, Enzo Grossi, Massimo Buscema, Maurizio D’Incalci, Ezia Bello, Gennaro Colella and Gabriella Camboni. Their work appears in journals such as Cancer Research, JBIC Journal of Biological Inorganic Chemistry, Annals of Biomedical Engineering, Neuroradiology and Medical Image Analysis.
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.