Gianluigi Patelli
- Surgery
- Pulmonary and Respiratory Medicine top 10%
- Radiology, Nuclear Medicine and Imaging top 10%
- Endocrinology, Diabetes and Metabolism top 10%
- Oncology
- Co-authors
- B DamascelliLaura FrigerioRodolfo LanocitaF GarbagnatiCarlo SpreaficoGiovanni MauriClaudio Maurizio PacellaGiuseppe Di Tolla
- Topics
- COVID-19 diagnosis using AI (6 papers)Radiomics and Machine Learning in Medical Imaging (4 papers)Hepatocellular Carcinoma Treatment and Prognosis (4 papers)
- Journals
- SHILAP Revista de lepidopterologíaThe Journal of Clinical Endocrinology & MetabolismCancer
- Partner nations
- ItalyUnited StatesMalaysia
In The Last Decade
Gianluigi Patelli
28 papers receiving 767 citations
Peers
Comparison fields: 5 of 99
- Surgery 218
- Pulmonary and Respiratory Medicine 212
- Radiology, Nuclear Medicine and Imaging 190
- Endocrinology, Diabetes and Metabolism 137
- Oncology 128
Countries citing papers authored by Gianluigi Patelli
This map shows the geographic impact of Gianluigi Patelli'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 Gianluigi Patelli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gianluigi Patelli more than expected).
Fields of papers citing papers by Gianluigi Patelli
This network shows the impact of papers produced by Gianluigi Patelli. 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 Gianluigi Patelli. The network helps show where Gianluigi Patelli may publish in the future.
Co-authorship network of co-authors of Gianluigi Patelli
This figure shows the co-authorship network connecting the top 25 collaborators of Gianluigi Patelli. A scholar is included among the top collaborators of Gianluigi Patelli 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 Gianluigi Patelli. Gianluigi Patelli 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 | 3 | |
| 3 | 21 | |
| 4 | 35 | |
| 5 | 29 | |
| 6 | 82 | |
| 7 | 1 | |
| 8 | 38 | |
| 9 | 43 | |
| 10 | 47 | |
| 11 | 125 | |
| 12 | 12 | |
| 13 | 22 | |
| 14 | 20 | |
| 15 | 53 | |
| 16 | 106 | |
| 17 | 6 | |
| 18 | 15 | |
| 19 | 50 | |
| 20 | 39 |
About Gianluigi Patelli
Gianluigi Patelli is a scholar working on Urology, Emergency Medical Services and Internal Medicine, having authored 30 papers that have together received 794 indexed citations. Recurring topics across this work include COVID-19 diagnosis using AI (6 papers), Radiomics and Machine Learning in Medical Imaging (4 papers) and Hepatocellular Carcinoma Treatment and Prognosis (4 papers). The work is most often cited by research in Health Informatics (31 citations), Urology (86 citations) and Radiology, Nuclear Medicine and Imaging (190 citations). Gianluigi Patelli has collaborated with scholars based in Italy, United States and Malaysia. Frequent co-authors include B Damascelli, Laura Frigerio, Rodolfo Lanocita, F Garbagnati, Carlo Spreafico, Giovanni Mauri, Claudio Maurizio Pacella, Giuseppe Di Tolla, Salvatore Cappabianca and Fabrizio Urraro. Their work appears in journals such as SHILAP Revista de lepidopterología, The Journal of Clinical Endocrinology & Metabolism and Cancer.
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.