Valentina Bellini
- Health Informatics top 0.05%
- Artificial Intelligence top 5%
- Radiology, Nuclear Medicine and Imaging top 5%
- Surgery
- Cardiology and Cardiovascular Medicine top 10%
- Co-authors
- Elena BignamiMarco CascellaJonathan MontomoliFederico SemeraroMarina ValenteDario BugadaOrnella PiazzaMarco Baciarello
- Topics
- Artificial Intelligence in Healthcare and Education (25 papers)Cardiac, Anesthesia and Surgical Outcomes (22 papers)Surgical Simulation and Training (11 papers)
- Partner nations
- ItalyUnited StatesAustralia
In The Last Decade
Valentina Bellini
53 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 127
- Health Informatics 709
- Artificial Intelligence 359
- Radiology, Nuclear Medicine and Imaging 328
- Surgery 277
- Cardiology and Cardiovascular Medicine 236
Countries citing papers authored by Valentina Bellini
This map shows the geographic impact of Valentina Bellini'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 Valentina Bellini with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Valentina Bellini more than expected).
Fields of papers citing papers by Valentina Bellini
This network shows the impact of papers produced by Valentina Bellini. 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 Valentina Bellini. The network helps show where Valentina Bellini may publish in the future.
Co-authorship network of co-authors of Valentina Bellini
This figure shows the co-authorship network connecting the top 25 collaborators of Valentina Bellini. A scholar is included among the top collaborators of Valentina Bellini 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 Valentina Bellini. Valentina Bellini 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 | 0 | |
| 3 | 10 | |
| 4 | 29 | |
| 5 | 2 | |
| 6 | The Breakthrough of Large Language Models Release for Medical Applications: 1-Year Timeline and Perspectivesbreakdown → | 100 |
| 7 | Evaluating the Feasibility of ChatGPT in Healthcare: An Analysis of Multiple Clinical and Research Scenariosbreakdown → | 656 |
| 8 | 1 | |
| 9 | 1 | |
| 10 | 1 | |
| 11 | 5 | |
| 12 | 8 | |
| 13 | 9 | |
| 14 | 39 | |
| 15 | 0 | |
| 16 | 1 | |
| 17 | 25 | |
| 18 | 8 | |
| 19 | 58 | |
| 20 | 25 |
About Valentina Bellini
Valentina Bellini is a scholar working on Health Informatics, Cardiology and Cardiovascular Medicine and Family Practice, having authored 63 papers that have together received 1.3k indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare and Education (25 papers), Cardiac, Anesthesia and Surgical Outcomes (22 papers) and Surgical Simulation and Training (11 papers). The work is most often cited by research in Health Informatics (709 citations), Family Practice (48 citations) and Radiology, Nuclear Medicine and Imaging (328 citations). Valentina Bellini has collaborated with scholars based in Italy, United States and Australia. Frequent co-authors include Elena Bignami, Marco Cascella, Jonathan Montomoli, Federico Semeraro, Marina Valente, Dario Bugada, Ornella Piazza, Marco Baciarello, Monica Mordonini and Ferdinando Luca Lorini. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE 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.