Gian Mauro Sacchetti
- Radiology, Nuclear Medicine and Imaging top 10%
- Pulmonary and Respiratory Medicine
- Physiology
- Surgery
- Oncology
- Co-authors
- Marco BrambillaRoberta MatheoudEugenio IngleseAlessandro CarrieroLucia LevaPatrizia GandolfoC SeccoAlessandro Stecco
- Topics
- Medical Imaging Techniques and Applications (11 papers)Radiomics and Machine Learning in Medical Imaging (5 papers)Advanced X-ray and CT Imaging (5 papers)
- Cited by
- Radiology, Nuclear Medicine and ImagingPulmonary and Respiratory MedicineObstetrics and Gynecology
- Partner nations
- ItalyUnited StatesGermany
In The Last Decade
Gian Mauro Sacchetti
23 papers receiving 284 citations
Peers
Comparison fields: 5 of 60
- Radiology, Nuclear Medicine and Imaging 137
- Pulmonary and Respiratory Medicine 109
- Physiology 46
- Surgery 39
- Oncology 32
Countries citing papers authored by Gian Mauro Sacchetti
This map shows the geographic impact of Gian Mauro Sacchetti'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 Gian Mauro Sacchetti with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gian Mauro Sacchetti more than expected).
Fields of papers citing papers by Gian Mauro Sacchetti
This network shows the impact of papers produced by Gian Mauro Sacchetti. 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 Gian Mauro Sacchetti. The network helps show where Gian Mauro Sacchetti may publish in the future.
Co-authorship network of co-authors of Gian Mauro Sacchetti
This figure shows the co-authorship network connecting the top 25 collaborators of Gian Mauro Sacchetti. A scholar is included among the top collaborators of Gian Mauro Sacchetti 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 Gian Mauro Sacchetti. Gian Mauro Sacchetti is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 2 | |
| 4 | 3 | |
| 5 | 0 | |
| 6 | 1 | |
| 7 | 0 | |
| 8 | 5 | |
| 9 | 6 | |
| 10 | 5 | |
| 11 | 18 | |
| 12 | 2 | |
| 13 | 18 | |
| 14 | 1 | |
| 15 | 39 | |
| 16 | 4 | |
| 17 | 18 | |
| 18 | 10 | |
| 19 | 8 | |
| 20 | 66 |
About Gian Mauro Sacchetti
Gian Mauro Sacchetti is a scholar working on Radiology, Nuclear Medicine and Imaging, Neurology and Radiation, having authored 26 papers that have together received 293 indexed citations. Recurring topics across this work include Medical Imaging Techniques and Applications (11 papers), Radiomics and Machine Learning in Medical Imaging (5 papers) and Advanced X-ray and CT Imaging (5 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (137 citations), Pulmonary and Respiratory Medicine (109 citations) and Obstetrics and Gynecology (26 citations). Gian Mauro Sacchetti has collaborated with scholars based in Italy, United States and Germany. Frequent co-authors include Marco Brambilla, Roberta Matheoud, Eugenio Inglese, Alessandro Carriero, Lucia Leva, Patrizia Gandolfo, C Secco, Alessandro Stecco, Gianmario Sambuceti and Francesco Buemi. Their work appears in journals such as Journal of Clinical Oncology, Annals of the Rheumatic Diseases and Neurobiology of Disease.
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.