Louis Deprez
- Radiology, Nuclear Medicine and Imaging top 10%
- Pulmonary and Respiratory Medicine
- Biomedical Engineering
- Oncology
- Artificial Intelligence
- Co-authors
- Pierre LovinfosseJulien GuiotDenis DanthinePhilippe LambinFadila ZerkaAkshayaa VaidyanathanRalph T. H. LeijenaarBenjamin Miraglio
- Topics
- Radiomics and Machine Learning in Medical Imaging (5 papers)COVID-19 diagnosis using AI (3 papers)Advanced X-ray and CT Imaging (2 papers)
- Cited by
- Health InformaticsRadiology, Nuclear Medicine and ImagingPulmonary and Respiratory Medicine
- Journals
- SHILAP Revista de lepidopterologíaAnnals of NeurologyMedicinal Research Reviews
- Partner nations
- BelgiumNetherlands
In The Last Decade
Louis Deprez
6 papers receiving 201 citations
Hit Papers
Peers
Comparison fields: 5 of 47
- Radiology, Nuclear Medicine and Imaging 160
- Pulmonary and Respiratory Medicine 63
- Biomedical Engineering 43
- Oncology 29
- Artificial Intelligence 23
Countries citing papers authored by Louis Deprez
This map shows the geographic impact of Louis Deprez'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 Louis Deprez with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Louis Deprez more than expected).
Fields of papers citing papers by Louis Deprez
This network shows the impact of papers produced by Louis Deprez. 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 Louis Deprez. The network helps show where Louis Deprez may publish in the future.
Co-authorship network of co-authors of Louis Deprez
This figure shows the co-authorship network connecting the top 25 collaborators of Louis Deprez. A scholar is included among the top collaborators of Louis Deprez 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 Louis Deprez. Louis Deprez 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 | 0 | |
| 4 | 6 | |
| 5 | 1 | |
| 6 | A review in radiomics: Making personalized medicine a reality via routine imagingbreakdown → | 192 |
| 7 | 1 | |
| 8 | [Chest radiological lesions in COVID-19 : from classical imaging to artificial intelligence]. | 1 |
About Louis Deprez
Louis Deprez is a scholar working on Radiology, Nuclear Medicine and Imaging, Genetics and Neurology, having authored 8 papers that have together received 202 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (5 papers), COVID-19 diagnosis using AI (3 papers) and Advanced X-ray and CT Imaging (2 papers). The work is most often cited by research in Health Informatics (14 citations), Radiology, Nuclear Medicine and Imaging (160 citations) and Pulmonary and Respiratory Medicine (63 citations). Louis Deprez has collaborated with scholars based in Belgium and Netherlands. Frequent co-authors include Pierre Lovinfosse, Julien Guiot, Denis Danthine, Philippe Lambin, Fadila Zerka, Akshayaa Vaidyanathan, Ralph T. H. Leijenaar, Benjamin Miraglio, Marta S. Ferreira and Wim Vos. Their work appears in journals such as SHILAP Revista de lepidopterología, Annals of Neurology and Medicinal Research Reviews.
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.