Michel E. Vandenberghe

922 total citations
19 papers, 393 citations indexed

About

Michel E. Vandenberghe is a scholar working on Radiology, Nuclear Medicine and Imaging, Molecular Biology and Artificial Intelligence. According to data from OpenAlex, Michel E. Vandenberghe has authored 19 papers receiving a total of 393 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Radiology, Nuclear Medicine and Imaging, 6 papers in Molecular Biology and 6 papers in Artificial Intelligence. Recurrent topics in Michel E. Vandenberghe's work include Cell Image Analysis Techniques (6 papers), AI in cancer detection (5 papers) and Radiomics and Machine Learning in Medical Imaging (3 papers). Michel E. Vandenberghe is often cited by papers focused on Cell Image Analysis Techniques (6 papers), AI in cancer detection (5 papers) and Radiomics and Machine Learning in Medical Imaging (3 papers). Michel E. Vandenberghe collaborates with scholars based in United Kingdom, France and Singapore. Michel E. Vandenberghe's co-authors include Marietta Scott, Craig Barker, Magnus Söderberg, Denis Balcerzak, Anna Sapino, Emad A. Rakha, Caterina Marchiò, Mohammed A. Aleskandarany, Ian O. Ellis and Paul Scorer and has published in prestigious journals such as Journal of Clinical Oncology, PLoS ONE and NeuroImage.

In The Last Decade

Michel E. Vandenberghe

18 papers receiving 383 citations

Peers

Michel E. Vandenberghe
Nathan Ing United States
Marcory van Dijk Netherlands
Quirine F. Manson Netherlands
Jerome Cheng United States
Daniel Heim Germany
Paul van Diest Netherlands
Zhaoxuan Ma United States
Venkata N. P. Vemuri United States
Zixiao Lu China
Liang-Bo Wang United States
Nathan Ing United States
Michel E. Vandenberghe
Citations per year, relative to Michel E. Vandenberghe Michel E. Vandenberghe (= 1×) peers Nathan Ing

Countries citing papers authored by Michel E. Vandenberghe

Since Specialization
Citations

This map shows the geographic impact of Michel E. Vandenberghe'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 Michel E. Vandenberghe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michel E. Vandenberghe more than expected).

Fields of papers citing papers by Michel E. Vandenberghe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michel E. Vandenberghe. 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 Michel E. Vandenberghe. The network helps show where Michel E. Vandenberghe may publish in the future.

Co-authorship network of co-authors of Michel E. Vandenberghe

This figure shows the co-authorship network connecting the top 25 collaborators of Michel E. Vandenberghe. A scholar is included among the top collaborators of Michel E. Vandenberghe 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 Michel E. Vandenberghe. Michel E. Vandenberghe is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

19 of 19 papers shown
1.
2.
Harel, Jonathan, Giuseppe Mallel, Michel E. Vandenberghe, et al.. (2023). Abstract P6-04-05: A fully automatic artificial intelligence system for accurate and reproducible HER2 IHC scoring in breast cancer. Cancer Research. 83(5_Supplement). P6–4. 1 indexed citations
3.
4.
Lee, Ching-Yi, Michel E. Vandenberghe, Marios A. Gavrielides, et al.. (2022). Usability of deep learning and H&E images predict disease outcome-emerging tool to optimize clinical trials. npj Precision Oncology. 6(1). 37–37. 27 indexed citations
5.
Scott, Marietta, Michel E. Vandenberghe, Paul Scorer, Anne-Marie Boothman, & Craig Barker. (2021). Prevalence of HER2 low in breast cancer subtypes using the VENTANA anti-HER2/neu (4B5) assay.. Journal of Clinical Oncology. 39(15_suppl). 1021–1021. 35 indexed citations
6.
Glass, Benjamin, Michel E. Vandenberghe, Marlon C. Rebelatto, et al.. (2021). Machine learning models to quantify HER2 for real-time tissue image analysis in prospective clinical trials.. Journal of Clinical Oncology. 39(15_suppl). 3061–3061. 4 indexed citations
7.
Ng, Felicia, Michel E. Vandenberghe, Guillem Portella, et al.. (2020). MINERVA: Learning the Rules of HLA Class I Peptide Presentation in Tumors with Convolutional Neural Networks and Transfer Learning. SSRN Electronic Journal. 1 indexed citations
8.
Vandenberghe, Michel E., et al.. (2019). Fast fluorescence in situ hybridisation for the enhanced detection of MET in non-small cell lung cancer. PLoS ONE. 14(10). e0223926–e0223926. 8 indexed citations
9.
Aleskandarany, Mohammed A., Michel E. Vandenberghe, Caterina Marchiò, et al.. (2018). Tumour Heterogeneity of Breast Cancer: From Morphology to Personalised Medicine. Pathobiology. 85(1-2). 23–34. 79 indexed citations
10.
Vandenberghe, Michel E., Anne‐Sophie Hérard, Florent Letronne, et al.. (2018). Voxel-Based Statistical Analysis of 3D Immunostained Tissue Imaging. Frontiers in Neuroscience. 12. 754–754. 7 indexed citations
11.
Balbastre, Yaël, Denis Rivière, Clara Fischer, et al.. (2017). A validation dataset for Macaque brain MRI segmentation. Data in Brief. 16. 37–42. 3 indexed citations
12.
Vandenberghe, Michel E., et al.. (2017). Relevance of deep learning to facilitate the diagnosis of HER2 status in breast cancer. Scientific Reports. 7(1). 45938–45938. 148 indexed citations
13.
Balbastre, Yaël, Denis Rivière, Clara Fischer, et al.. (2017). Primatologist: A modular segmentation pipeline for macaque brain morphometry. NeuroImage. 162. 306–321. 9 indexed citations
14.
Santin, Mathieu, Michel E. Vandenberghe, Anne‐Sophie Hérard, et al.. (2016). In Vivo Detection of Amyloid Plaques by Gadolinium-Stained MRI Can Be Used to Demonstrate the Efficacy of an Anti-amyloid Immunotherapy. Frontiers in Aging Neuroscience. 8. 55–55. 14 indexed citations
15.
Vandenberghe, Michel E., Anne‐Sophie Hérard, Mathieu Santin, et al.. (2016). High-throughput 3D whole-brain quantitative histopathology in rodents. Scientific Reports. 6(1). 20958–20958. 30 indexed citations
16.
Vandenberghe, Michel E., Yaël Balbastre, Philippe Hantraye, et al.. (2016). Automated cell individualization and counting in cerebral microscopic images. HAL (Le Centre pour la Communication Scientifique Directe). 3389–3393. 5 indexed citations
17.
Vandenberghe, Michel E., Yaël Balbastre, Anne‐Sophie Hérard, et al.. (2015). Robust supervised segmentation of neuropathology whole-slide microscopy images. PubMed. 2015. 3851–3854. 6 indexed citations
18.
Vandenberghe, Michel E.. (2003). Enjeux politiques et dimensions socio-techniques du travail d'inspection dans l'administration sanitaire et sociale. Politiques et management public. 21(4). 15–40.
19.
Nakatsu, K., et al.. (1986). Endothelium-dependent relaxation of rabbit aorta by acetylcholine requires ethylenediaminetetraacetic acid. Canadian Journal of Physiology and Pharmacology. 64(7). 1050–1052. 6 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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