Vincenzo L’Imperio
- Health Informatics top 2%
- Nephrology top 5%
- Renal Diseases and Glomerulopathies 22
- Chronic Kidney Disease and Diabetes 8
-
- Radiomics and Machine Learning in Medical Imaging 16
- Biophysics top 5%
- Artificial Intelligence top 5%
- AI in cancer detection 16
-
- Thyroid Cancer Diagnosis and Treatment 15
-
- Amyloidosis: Diagnosis, Treatment, Outcomes 14
-
- Advanced Proteomics Techniques and Applications 11
-
- Vasculitis and related conditions 10
- Co-authors
- Fabio PagniAndrew SmithFulvio MagniFilippo FraggettaClizia ChinelloFederico PieruzziAlessandro CaputoFrancesca Bono
- Journals
- SHILAP Revista de lepidopterología (3 papers)Scientific Reports (1 paper)International Journal of Molecular Sciences (4 papers)
- Partner nations
- ItalyUnited StatesGermany
In The Last Decade
Vincenzo L’Imperio
88 papers receiving 944 citations
Peers
Comparison fields: 5 of 87
- Health Informatics 62
- Nephrology 150
- Radiology, Nuclear Medicine and Imaging 241
- Biophysics 56
- Artificial Intelligence 245
Countries citing papers authored by Vincenzo L’Imperio
This map shows the geographic impact of Vincenzo L’Imperio'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 Vincenzo L’Imperio with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vincenzo L’Imperio more than expected).
Fields of papers citing papers by Vincenzo L’Imperio
This network shows the impact of papers produced by Vincenzo L’Imperio. 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 Vincenzo L’Imperio. The network helps show where Vincenzo L’Imperio may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Vincenzo L’Imperio, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 0 | |
| 4 | 2024 | 0 | |
| 5 | 2024 | 2 | |
| 6 | 2024 | 2 | |
| 7 | 2024 | 0 | |
| 8 | 2024 | 7 | |
| 9 | 2024 | 1 | |
| 10 | 2024 | 30 | |
| 11 | 2023 | 4 | |
| 12 | 2023 | 12 | |
| 13 | 2023 | 8 | |
| 14 | 2023 | 27 | |
| 15 | 2023 | 3 | |
| 16 | 2023 | 5 | |
| 17 | 2023 | 13 | |
| 18 | 2022 | 2 | |
| 19 | 2022 | 16 | |
| 20 | 2021 | 19 |
About Vincenzo L’Imperio
Vincenzo L’Imperio is a scholar working on Nephrology, Health Informatics and Transplantation, having authored 103 papers that have together received 953 indexed citations. Recurring topics across this work include Renal Diseases and Glomerulopathies (22 papers), Radiomics and Machine Learning in Medical Imaging (16 papers), AI in cancer detection (16 papers), Thyroid Cancer Diagnosis and Treatment (15 papers), Amyloidosis: Diagnosis, Treatment, Outcomes (14 papers), Advanced Proteomics Techniques and Applications (11 papers), Vasculitis and related conditions (10 papers) and Chronic Kidney Disease and Diabetes (8 papers). The work is most often cited by research in Health Informatics (62 citations), Nephrology (150 citations) and Radiology, Nuclear Medicine and Imaging (241 citations). Vincenzo L’Imperio has collaborated with scholars based in Italy, United States and Germany. Frequent co-authors include Fabio Pagni, Andrew Smith, Fulvio Magni, Filippo Fraggetta, Clizia Chinello, Federico Pieruzzi, Alessandro Caputo, Francesca Bono, Franco Ferrario and Albino Eccher. Their work appears in journals such as SHILAP Revista de lepidopterología, Scientific Reports and International Journal of Molecular Sciences.
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.