LJ van't Veer

1.1k total citations
18 papers, 112 citations indexed

About

LJ van't Veer is a scholar working on Cancer Research, Genetics and Pulmonary and Respiratory Medicine. According to data from OpenAlex, LJ van't Veer has authored 18 papers receiving a total of 112 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Cancer Research, 7 papers in Genetics and 6 papers in Pulmonary and Respiratory Medicine. Recurrent topics in LJ van't Veer's work include Breast Cancer Treatment Studies (6 papers), BRCA gene mutations in cancer (5 papers) and Radiomics and Machine Learning in Medical Imaging (3 papers). LJ van't Veer is often cited by papers focused on Breast Cancer Treatment Studies (6 papers), BRCA gene mutations in cancer (5 papers) and Radiomics and Machine Learning in Medical Imaging (3 papers). LJ van't Veer collaborates with scholars based in United States, Netherlands and Sweden. LJ van't Veer's co-authors include W. J. Mooi, Nico van Zandwijk, Robert J.C. Slebos, Lucie Boerrigter, Sjoerd Rodenhuis, Bert Top, Gabriel Rinnerthaler, Zsuzsanna Bagó-Horváth, Martin Filipits and Wolfgang Hulla and has published in prestigious journals such as Journal of Clinical Oncology, Cancer Research and Annals of Oncology.

In The Last Decade

LJ van't Veer

18 papers receiving 107 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
LJ van't Veer United States 4 66 62 45 34 12 18 112
Laia Serrano Spain 7 55 0.8× 73 1.2× 48 1.1× 64 1.9× 10 0.8× 9 156
Rowena Sharpe United Kingdom 3 51 0.8× 76 1.2× 58 1.3× 71 2.1× 7 0.6× 6 137
Masyar Gardizi Germany 5 65 1.0× 85 1.4× 58 1.3× 38 1.1× 12 1.0× 9 124
Bryan Johnson United States 3 90 1.4× 46 0.7× 66 1.5× 22 0.6× 12 1.0× 7 126
Michel Velez United States 6 54 0.8× 50 0.8× 71 1.6× 24 0.7× 8 0.7× 16 110
Gongyan Chen China 7 90 1.4× 85 1.4× 76 1.7× 36 1.1× 8 0.7× 13 163
Marc Bos Germany 5 84 1.3× 90 1.5× 82 1.8× 43 1.3× 17 1.4× 12 162
Giada Targato Italy 4 79 1.2× 61 1.0× 36 0.8× 29 0.9× 14 1.2× 18 119
Lucia Mentuccia Italy 8 133 2.0× 63 1.0× 37 0.8× 75 2.2× 16 1.3× 22 192
Chuangzhou Rao China 7 55 0.8× 61 1.0× 78 1.7× 82 2.4× 12 1.0× 23 149

Countries citing papers authored by LJ van't Veer

Since Specialization
Citations

This map shows the geographic impact of LJ van't Veer'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 LJ van't Veer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites LJ van't Veer more than expected).

Fields of papers citing papers by LJ van't Veer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by LJ van't Veer. 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 LJ van't Veer. The network helps show where LJ van't Veer may publish in the future.

Co-authorship network of co-authors of LJ van't Veer

This figure shows the co-authorship network connecting the top 25 collaborators of LJ van't Veer. A scholar is included among the top collaborators of LJ van't Veer 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 LJ van't Veer. LJ van't Veer is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
1.
Dubsky, Peter, LJ van't Veer, Michael Gnant, et al.. (2021). A clinical validation study of MammaPrint in hormone receptor-positive breast cancer from the Austrian Breast and Colorectal Cancer Study Group 8 (ABCSG-8) biomarker cohort. ESMO Open. 6(1). 100006–100006. 10 indexed citations
2.
Shieh, Yiwey, Elad Ziv, Martin Eklund, et al.. (2018). Abstract P3-09-02: Risk stratification using clinical risk factors and genetic variants in a personalized screening trial. Cancer Research. 78(4_Supplement). P3–9. 1 indexed citations
3.
Rutgers, Emiel J., Coralie Poncet, Fátima Cardoso, et al.. (2018). Very low risk of locoregional breast cancer recurrence in the EORTC 10041/BIG 03-04 MINDACT trial: Analysis of risk factors including the 70-gene signature. European Journal of Cancer. 92. S7–S8. 2 indexed citations
4.
Yau, Christina, LJ van't Veer, Bo Nordenskjöld, et al.. (2017). Abstract PD7-02: Identification of breast cancers with an indolent disease course: 70 gene indolent threshold validation in a Swedish randomized trial of tamoxifen vs. not, with 20 year outcomes. Cancer Research. 77(4_Supplement). PD7–2. 1 indexed citations
5.
Fiscalini, Allison Stover, LJ van't Veer, Alexander D. Borowsky, et al.. (2016). Abstract P3-10-01: A pilot feasibility study of the WISDOM study, a preference-tolerant randomized controlled trial evaluating a risk-based breast cancer screening strategy. Cancer Research. 76(4_Supplement). P3–10. 1 indexed citations
6.
7.
Wesseling, Jelle, et al.. (2012). Abstract P2-10-42: Gene expression profiling to predict the risk of locoregional recurrence in breast cancer. Cancer Research. 72(24_Supplement). P2–10. 3 indexed citations
8.
Schmidt, Marjanka K., Emiel J. Rutgers, Fátima Cardoso, et al.. (2012). Abstract P3-02-01: Mammographic Screening: Good Prognosis Tumor Biology in Screen-detected Breast Cancers. Cancer Research. 72(24_Supplement). P3–2. 1 indexed citations
9.
Saghatchian, Mahasti, Lorenza Mittempergher, Stefan Michiels, et al.. (2012). Abstract P4-09-05: Microarray anlyses of breast cancers identify CH25H, a cholesterol gene, as a potential marker and target for late metastatic reccurences.. Cancer Research. 72(24_Supplement). P4–9. 1 indexed citations
10.
Schmidt, Marjanka K., et al.. (2011). S4-2: The Risk of Contralateral Breast Cancer in BRCA1/2 Carriers Compared to Non-BRCA1/2 Carriers in an Unselected Cohort.. Cancer Research. 71(24_Supplement). S4–2. 1 indexed citations
11.
Simón, Iris, Simon Tian, Vı́ctor Moreno, et al.. (2011). The role of activating mutations of KRAS, BRAF, and PIK3CA pathway convergence at the transcriptional level and prediction of treatment response to cetuximab in colorectal cancer.. Journal of Clinical Oncology. 29(15_suppl). 3534–3534. 4 indexed citations
12.
Veer, LJ van't, et al.. (2009). Biology of breast cancers that present as interval cancers and at young age should inform how we approach early detection and prevention.. Cancer Research. 69(2_Supplement). 6034–6034. 2 indexed citations
13.
Reyal, Fabien, Nicola J. Armstrong, Stella Mook, et al.. (2009). A comprehensive analysis of nine prognostic signatures reveals the high classification instability in breast cancer.. Cancer Research. 69(2_Supplement). 2026–2026. 3 indexed citations
14.
15.
Pusztai, L., Christos Hatzis, Fátima Cardoso, et al.. (2008). Combined use of genomic prognostic and treatment response predictors in breast cancer. Journal of Clinical Oncology. 26(15_suppl). 527–527. 4 indexed citations
16.
Capella, Matías, Ryan K. van Laar, Corrie A.M. Marijnen, et al.. (2007). Prognosis prediction of stage II colon cancer by gene expression profiling. Annals of Oncology. 18. 2 indexed citations
17.
Rodenhuis, Sjoerd, Lucie Boerrigter, Bert Top, et al.. (1997). Mutational activation of the K-ras oncogene and the effect of chemotherapy in advanced adenocarcinoma of the lung: a prospective study.. Journal of Clinical Oncology. 15(1). 285–291. 73 indexed citations
18.
Hogervorst, Frans B.L., M J Ligtenberg, Gijs R. van den Brink, et al.. (1997). 0-8. Germ-line mutations in BRCA1 and BRCA2 are seldom found in `unilateral breast cancer only' families. The Breast. 6(4). 227–227. 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Laia Serrano Breakdown of academic impact, for papers by Rowena Sharpe Breakdown of academic impact, for papers by Masyar Gardizi Breakdown of academic impact, for papers by Bryan Johnson Breakdown of academic impact, for papers by Michel Velez Breakdown of academic impact, for papers by Gongyan Chen Breakdown of academic impact, for papers by Marc Bos Breakdown of academic impact, for papers by Giada Targato Breakdown of academic impact, for papers by Lucia Mentuccia Breakdown of academic impact, for papers by Chuangzhou Rao
Rankless by CCL
2026