Chiara Trentin
- Pulmonary and Respiratory Medicine top 10%
- Surgery
- Radiology, Nuclear Medicine and Imaging top 10%
- Oncology
- Pathology and Forensic Medicine top 10%
- Co-authors
- Enrico CassanoGiovanni CorsoViviana GalimbertiPaolo VeronesiMattia IntraOrazio CaffoValeria DominelliAntonello Veccia
- Topics
- Radiomics and Machine Learning in Medical Imaging (8 papers)Breast Lesions and Carcinomas (7 papers)AI in cancer detection (5 papers)
- Journals
- Journal of Clinical OncologySHILAP Revista de lepidopterologíaAnnals of Oncology
- Partner nations
- ItalyNetherlandsUnited Kingdom
In The Last Decade
Chiara Trentin
41 papers receiving 599 citations
Peers
Comparison fields: 5 of 74
- Pulmonary and Respiratory Medicine 211
- Surgery 158
- Radiology, Nuclear Medicine and Imaging 149
- Oncology 148
- Pathology and Forensic Medicine 146
Countries citing papers authored by Chiara Trentin
This map shows the geographic impact of Chiara Trentin'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 Chiara Trentin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chiara Trentin more than expected).
Fields of papers citing papers by Chiara Trentin
This network shows the impact of papers produced by Chiara Trentin. 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 Chiara Trentin. The network helps show where Chiara Trentin may publish in the future.
Co-authorship network of co-authors of Chiara Trentin
This figure shows the co-authorship network connecting the top 25 collaborators of Chiara Trentin. A scholar is included among the top collaborators of Chiara Trentin 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 Chiara Trentin. Chiara Trentin 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 | 9 | |
| 3 | 15 | |
| 4 | 40 | |
| 5 | 2 | |
| 6 | 4 | |
| 7 | 8 | |
| 8 | 5 | |
| 9 | 9 | |
| 10 | 14 | |
| 11 | 20 | |
| 12 | 1 | |
| 13 | 32 | |
| 14 | 30 | |
| 15 | 5 | |
| 16 | 44 | |
| 17 | 38 | |
| 18 | 0 | |
| 19 | 10 | |
| 20 | 7 |
About Chiara Trentin
Chiara Trentin is a scholar working on Health Informatics, Pathology and Forensic Medicine and Radiology, Nuclear Medicine and Imaging, having authored 44 papers that have together received 615 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (8 papers), Breast Lesions and Carcinomas (7 papers) and AI in cancer detection (5 papers). The work is most often cited by research in Health Informatics (17 citations), Cancer Research (134 citations) and Pathology and Forensic Medicine (146 citations). Chiara Trentin has collaborated with scholars based in Italy, Netherlands and United Kingdom. Frequent co-authors include Enrico Cassano, Giovanni Corso, Viviana Galimberti, Paolo Veronesi, Mattia Intra, Orazio Caffo, Valeria Dominelli, Antonello Veccia, Alessandro Del Maschio and Francesco De Cobelli. Their work appears in journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Annals of Oncology.
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.