Nicolas Loménie
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Radiology, Nuclear Medicine and Imaging top 10%
- Biophysics top 5%
- Molecular Biology
- Co-authors
- Daniel RacoceanuHumayun IrshadAntoine VeillardZhaohui HuangGeorges StamonJulien CaldéraroMaria Chiara MaiuriChristophe Klein
- Topics
- AI in cancer detection (9 papers)Image Retrieval and Classification Techniques (7 papers)Cell Image Analysis Techniques (6 papers)
In The Last Decade
Nicolas Loménie
26 papers receiving 454 citations
Peers
Comparison fields: 5 of 77
- Artificial Intelligence 303
- Computer Vision and Pattern Recognition 203
- Radiology, Nuclear Medicine and Imaging 169
- Biophysics 92
- Molecular Biology 55
Countries citing papers authored by Nicolas Loménie
This map shows the geographic impact of Nicolas Loménie'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 Nicolas Loménie with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nicolas Loménie more than expected).
Fields of papers citing papers by Nicolas Loménie
This network shows the impact of papers produced by Nicolas Loménie. 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 Nicolas Loménie. The network helps show where Nicolas Loménie may publish in the future.
Co-authorship network of co-authors of Nicolas Loménie
This figure shows the co-authorship network connecting the top 25 collaborators of Nicolas Loménie. A scholar is included among the top collaborators of Nicolas Loménie 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 Nicolas Loménie. Nicolas Loménie 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 | 1 | |
| 3 | 1 | |
| 4 | 72 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 14 | |
| 9 | 1 | |
| 10 | 217 | |
| 11 | 3 | |
| 12 | 1 | |
| 13 | 46 | |
| 14 | 10 | |
| 15 | 2 | |
| 16 | 6 | |
| 17 | 12 | |
| 18 | An automatic system for the analysis of intercellular communication and early carcinogenesis. | 1 |
| 19 | 19 | |
| 20 | 5 |
About Nicolas Loménie
Nicolas Loménie is a scholar working on Biophysics, Health Informatics and Computer Vision and Pattern Recognition, having authored 29 papers that have together received 474 indexed citations. Recurring topics across this work include AI in cancer detection (9 papers), Image Retrieval and Classification Techniques (7 papers) and Cell Image Analysis Techniques (6 papers). The work is most often cited by research in Biophysics (92 citations), Computer Vision and Pattern Recognition (203 citations) and Artificial Intelligence (303 citations). Nicolas Loménie has collaborated with scholars based in France, Singapore and Belgium. Frequent co-authors include Daniel Racoceanu, Humayun Irshad, Antoine Veillard, Zhaohui Huang, Georges Stamon, Julien Caldéraro, Maria Chiara Maiuri, Christophe Klein, Qinghe Zeng and Güray Erus. Their work appears in journals such as Journal of Hepatology, Annals of Oncology and British Journal of Pharmacology.
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.