Louis Deprez

427 total citations · 1 hit paper
8 papers, 202 citations indexed

About

Louis Deprez is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Biomedical Engineering. According to data from OpenAlex, Louis Deprez has authored 8 papers receiving a total of 202 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Radiology, Nuclear Medicine and Imaging, 2 papers in Pulmonary and Respiratory Medicine and 2 papers in Biomedical Engineering. Recurrent topics in Louis Deprez's 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). Louis Deprez is often cited by papers focused on 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). Louis Deprez collaborates with scholars based in Belgium and Netherlands. Louis Deprez's 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 and has published in prestigious journals such as SHILAP Revista de lepidopterología, Annals of Neurology and Medicinal Research Reviews.

In The Last Decade

Louis Deprez

6 papers receiving 201 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A review in radiomics: Making personalized medicine a reality via routine imaging

2021 192 citations Julien Guiot, Akshayaa Vaidyanathan et al. Medicinal Research Reviews profile →

Peers

Louis Deprez

RNMI

PRM

BE

ONCOL

AI

Denis Danthine Belgium

Nathan Tsoutzidis Netherlands

Salvatore Claudio Fanni Italy

Iva Halilaj Netherlands

Konstantinos Ferentinos Cyprus

Zongrui Ma China

Dhakshinamoorthy Ganeshan United States

Mattia Zaffaroni Italy

Fabian Tollens Germany

Isabella Fornacon-Wood United Kingdom

Denis Danthine Belgium

Louis Deprez

162 ×1.0

RNMI

66 ×1.0

PRM

43 ×1.0

BE

29 ×1.0

ONCOL

24 ×1.0

AI

Citations per year, relative to Louis Deprez Louis Deprez (= 1×) peers Denis Danthine

Countries citing papers authored by Louis Deprez

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

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8 of 8 papers shown

1.

Deprez, Louis, et al.. (2025). Petroclival meningioma regression after combined oestrogen and nomegestrol acetate interruption. BMJ Case Reports. 18(1). e263529–e263529. 1 indexed citations

2.

Deprez, Louis, et al.. (2024). Brain Tumor Assessment. PET Clinics. 20(1). 165–174.

3.

Ly, Julien, et al.. (2023). Hemispheric Hypoperfusion in Immune Effector Cell‐Associated Neurotoxicity Syndrome following Chimeric Antigen Receptor T‐Cell Therapy. Annals of Neurology. 95(3). 617–619.

4.

Vaidyanathan, Akshayaa, Julien Guiot, Fadila Zerka, et al.. (2022). An externally validated fully automated deep learning algorithm to classify COVID-19 and other pneumonias on chest computed tomography. ERJ Open Research. 8(2). 579–2021. 6 indexed citations

5.

Deprez, Louis, et al.. (2021). Added Value of Dual-Energy CT in COVID-19 Pneumopathy. SHILAP Revista de lepidopterología. 105(1). 62–62. 1 indexed citations

6.

Guiot, Julien, Akshayaa Vaidyanathan, Louis Deprez, et al.. (2021). A review in radiomics: Making personalized medicine a reality via routine imaging. Medicinal Research Reviews. 42(1). 426–440. 192 indexed citations breakdown →

7.

Zerka, Fadila, Akshayaa Vaidyanathan, Julien Guiot, et al.. (2020). Late Breaking Abstract - Development and validation of an automated radiomic CT signature for detecting?COVID-19. 4152–4152. 1 indexed citations

8.

Guiot, Julien, Denis Danthine, Louis Deprez, et al.. (2020). [Chest radiological lesions in COVID-19 : from classical imaging to artificial intelligence].. PubMed. 75(S1). 81–85. 1 indexed citations

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.

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