Francesco Pucciarelli
- Radiology, Nuclear Medicine and Imaging top 2%
- Infectious Diseases top 5%
- Oncology
- Neurology top 10%
- Pulmonary and Respiratory Medicine
- Co-authors
- Michela PoliciDamiano CarusoAndrea LaghiMarta ZerunianGisella GuidoTiziano PolidoriBenedetta BracciCarlotta Rucci
- Topics
- Radiomics and Machine Learning in Medical Imaging (9 papers)COVID-19 Clinical Research Studies (6 papers)COVID-19 diagnosis using AI (5 papers)
- Cited by
- Radiology, Nuclear Medicine and ImagingCritical Care and Intensive Care MedicineInfectious Diseases
- Partner nations
- ItalyUnited StatesUnited Kingdom
In The Last Decade
Francesco Pucciarelli
17 papers receiving 847 citations
Hit Papers
Peers
Comparison fields: 5 of 82
- Radiology, Nuclear Medicine and Imaging 535
- Infectious Diseases 390
- Oncology 194
- Neurology 149
- Pulmonary and Respiratory Medicine 128
Countries citing papers authored by Francesco Pucciarelli
This map shows the geographic impact of Francesco Pucciarelli'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 Francesco Pucciarelli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Francesco Pucciarelli more than expected).
Fields of papers citing papers by Francesco Pucciarelli
This network shows the impact of papers produced by Francesco Pucciarelli. 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 Francesco Pucciarelli. The network helps show where Francesco Pucciarelli may publish in the future.
Co-authorship network of co-authors of Francesco Pucciarelli
This figure shows the co-authorship network connecting the top 25 collaborators of Francesco Pucciarelli. A scholar is included among the top collaborators of Francesco Pucciarelli 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 Francesco Pucciarelli. Francesco Pucciarelli 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 | 0 | |
| 4 | 1 | |
| 5 | 12 | |
| 6 | 12 | |
| 7 | 28 | |
| 8 | 4 | |
| 9 | 42 | |
| 10 | 7 | |
| 11 | 8 | |
| 12 | 20 | |
| 13 | 14 | |
| 14 | 8 | |
| 15 | 25 | |
| 16 | 13 | |
| 17 | 38 | |
| 18 | 33 | |
| 19 | 149 | |
| 20 | Chest CT Features of COVID-19 in Rome, Italybreakdown → | 416 |
About Francesco Pucciarelli
Francesco Pucciarelli is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Infectious Diseases, having authored 21 papers that have together received 868 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (9 papers), COVID-19 Clinical Research Studies (6 papers) and COVID-19 diagnosis using AI (5 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (535 citations), Critical Care and Intensive Care Medicine (112 citations) and Infectious Diseases (390 citations). Francesco Pucciarelli has collaborated with scholars based in Italy, United States and United Kingdom. Frequent co-authors include Michela Polici, Damiano Caruso, Andrea Laghi, Marta Zerunian, Gisella Guido, Tiziano Polidori, Benedetta Bracci, Carlotta Rucci, Chiara De Dominicis and Mariarita Tarallo. Their work appears in journals such as Radiology, Metabolism and BioMed Research International.
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.