Niccolò Marini
- Artificial Intelligence top 10%
- Radiology, Nuclear Medicine and Imaging
- Computer Vision and Pattern Recognition top 10%
- Biomedical Engineering
- Pulmonary and Respiratory Medicine
- Co-authors
- Henning MüllerManfredo AtzoriSebastian OtáloraFrancesco CiompiMarek WodzińskiGianmaria SilvelloStéphane Marchand‐MailletMart van Rijthoven
- Topics
- AI in cancer detection (13 papers)Radiomics and Machine Learning in Medical Imaging (10 papers)Digital Imaging for Blood Diseases (8 papers)
- Partner nations
- SwitzerlandItalyNetherlands
In The Last Decade
Niccolò Marini
18 papers receiving 211 citations
Peers
Comparison fields: 5 of 52
- Artificial Intelligence 157
- Radiology, Nuclear Medicine and Imaging 102
- Computer Vision and Pattern Recognition 74
- Biomedical Engineering 30
- Pulmonary and Respiratory Medicine 27
Countries citing papers authored by Niccolò Marini
This map shows the geographic impact of Niccolò Marini'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 Niccolò Marini with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Niccolò Marini more than expected).
Fields of papers citing papers by Niccolò Marini
This network shows the impact of papers produced by Niccolò Marini. 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 Niccolò Marini. The network helps show where Niccolò Marini may publish in the future.
Co-authorship network of co-authors of Niccolò Marini
This figure shows the co-authorship network connecting the top 25 collaborators of Niccolò Marini. A scholar is included among the top collaborators of Niccolò Marini 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 Niccolò Marini. Niccolò Marini 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 | 9 | |
| 4 | 4 | |
| 5 | 4 | |
| 6 | 0 | |
| 7 | 5 | |
| 8 | 1 | |
| 9 | 24 | |
| 10 | 9 | |
| 11 | 2 | |
| 12 | 40 | |
| 13 | 10 | |
| 14 | 3 | |
| 15 | 3 | |
| 16 | 49 | |
| 17 | 21 | |
| 18 | Multi-Scale Task Multiple Instance Learning for the Classification of Digital Pathology Images with Global Annotations | 6 |
| 19 | 8 | |
| 20 | 14 |
About Niccolò Marini
Niccolò Marini is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 20 papers that have together received 213 indexed citations. Recurring topics across this work include AI in cancer detection (13 papers), Radiomics and Machine Learning in Medical Imaging (10 papers) and Digital Imaging for Blood Diseases (8 papers). The work is most often cited by research in Artificial Intelligence (157 citations), Biophysics (27 citations) and Radiology, Nuclear Medicine and Imaging (102 citations). Niccolò Marini has collaborated with scholars based in Switzerland, Italy and Netherlands. Frequent co-authors include Henning Müller, Manfredo Atzori, Sebastian Otálora, Francesco Ciompi, Marek Wodziński, Gianmaria Silvello, Stéphane Marchand‐Maillet, Mart van Rijthoven, Stefano Marchesin and Jeroen van der Laak. Their work appears in journals such as Sensors, Medical Image Analysis and Computer Methods and Programs in Biomedicine.
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.