Carlotta Rucci
- Radiology, Nuclear Medicine and Imaging top 5%
- Infectious Diseases top 5%
- Oncology
- Critical Care and Intensive Care Medicine top 5%
- Pulmonary and Respiratory Medicine
- Co-authors
- Damiano CarusoGisella GuidoTiziano PolidoriAndrea LaghiMarta ZerunianMichela PoliciFrancesco PucciarelliBenedetta Bracci
- Topics
- Radiomics and Machine Learning in Medical Imaging (6 papers)COVID-19 Clinical Research Studies (5 papers)COVID-19 diagnosis using AI (5 papers)
- Cited by
- Radiology, Nuclear Medicine and ImagingCritical Care and Intensive Care MedicineHealth Informatics
- Partner nations
- ItalyUnited StatesUnited Kingdom
In The Last Decade
Carlotta Rucci
16 papers receiving 638 citations
Hit Papers
Peers
Comparison fields: 5 of 68
- Radiology, Nuclear Medicine and Imaging 476
- Infectious Diseases 297
- Oncology 152
- Critical Care and Intensive Care Medicine 106
- Pulmonary and Respiratory Medicine 103
Countries citing papers authored by Carlotta Rucci
This map shows the geographic impact of Carlotta Rucci'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 Carlotta Rucci with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Carlotta Rucci more than expected).
Fields of papers citing papers by Carlotta Rucci
This network shows the impact of papers produced by Carlotta Rucci. 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 Carlotta Rucci. The network helps show where Carlotta Rucci may publish in the future.
Co-authorship network of co-authors of Carlotta Rucci
This figure shows the co-authorship network connecting the top 25 collaborators of Carlotta Rucci. A scholar is included among the top collaborators of Carlotta Rucci 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 Carlotta Rucci. Carlotta Rucci is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 22 | |
| 2 | 28 | |
| 3 | 1 | |
| 4 | 8 | |
| 5 | 20 | |
| 6 | 0 | |
| 7 | 2 | |
| 8 | 25 | |
| 9 | 13 | |
| 10 | 38 | |
| 11 | 38 | |
| 12 | 33 | |
| 13 | Chest CT Features of COVID-19 in Rome, Italybreakdown → | 416 |
| 14 | 3 | |
| 15 | 1 | |
| 16 | 3 | |
| 17 | 6 |
About Carlotta Rucci
Carlotta Rucci is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Infectious Diseases, having authored 17 papers that have together received 657 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (6 papers), COVID-19 Clinical Research Studies (5 papers) and COVID-19 diagnosis using AI (5 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (476 citations), Critical Care and Intensive Care Medicine (106 citations) and Health Informatics (22 citations). Carlotta Rucci has collaborated with scholars based in Italy, United States and United Kingdom. Frequent co-authors include Damiano Caruso, Gisella Guido, Tiziano Polidori, Andrea Laghi, Marta Zerunian, Michela Polici, Francesco Pucciarelli, Benedetta Bracci, Chiara De Dominicis and Matteo Nicolai. Their work appears in journals such as Radiology, Advances in experimental medicine and biology 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.