Leonardo Rundo
- Radiology, Nuclear Medicine and Imaging top 1%
- Artificial Intelligence top 1%
- Computer Vision and Pattern Recognition top 1%
- Neurology top 2%
- Pulmonary and Respiratory Medicine top 5%
- Co-authors
- Evis SalaCarmelo MilitelloGiancarlo MauriMichael YeungCarola‐Bibiane SchönliebSalvatore VitabileChanghee HanHideki Nakayama
- Topics
- Radiomics and Machine Learning in Medical Imaging (43 papers)AI in cancer detection (24 papers)Advanced Neural Network Applications (12 papers)
- Partner nations
- ItalyUnited KingdomUnited States
In The Last Decade
Leonardo Rundo
100 papers receiving 3.2k citations
Hit Papers
Peers
Comparison fields: 5 of 170
- Radiology, Nuclear Medicine and Imaging 1.4k
- Artificial Intelligence 1.2k
- Computer Vision and Pattern Recognition 1.0k
- Neurology 518
- Pulmonary and Respiratory Medicine 437
Countries citing papers authored by Leonardo Rundo
This map shows the geographic impact of Leonardo Rundo'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 Leonardo Rundo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Leonardo Rundo more than expected).
Fields of papers citing papers by Leonardo Rundo
This network shows the impact of papers produced by Leonardo Rundo. 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 Leonardo Rundo. The network helps show where Leonardo Rundo may publish in the future.
Co-authorship network of co-authors of Leonardo Rundo
This figure shows the co-authorship network connecting the top 25 collaborators of Leonardo Rundo. A scholar is included among the top collaborators of Leonardo Rundo 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 Leonardo Rundo. Leonardo Rundo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 5 | |
| 3 | 1 | |
| 4 | 9 | |
| 5 | 30 | |
| 6 | 2 | |
| 7 | 2 | |
| 8 | 13 | |
| 9 | 47 | |
| 10 | 7 | |
| 11 | 6 | |
| 12 | 10 | |
| 13 | 12 | |
| 14 | 1 | |
| 15 | 39 | |
| 16 | 0 | |
| 17 | 17 | |
| 18 | 10 | |
| 19 | 36 | |
| 20 | 3 |
About Leonardo Rundo
Leonardo Rundo is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Biophysics, having authored 102 papers that have together received 3.3k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (43 papers), AI in cancer detection (24 papers) and Advanced Neural Network Applications (12 papers). The work is most often cited by research in Health Informatics (177 citations), Neurology (518 citations) and Radiology, Nuclear Medicine and Imaging (1.4k citations). Leonardo Rundo has collaborated with scholars based in Italy, United Kingdom and United States. Frequent co-authors include Evis Sala, Carmelo Militello, Giancarlo Mauri, Michael Yeung, Carola‐Bibiane Schönlieb, Salvatore Vitabile, Changhee Han, Hideki Nakayama, G. Russo and Andrea Tangherloni. Their work appears in journals such as Scientific Reports, Expert Systems with Applications and IEEE Access.
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.