Gregory Patrick Veldhuizen

1.7k total citations · 1 hit paper
24 papers, 784 citations indexed

About

Gregory Patrick Veldhuizen is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Oncology. According to data from OpenAlex, Gregory Patrick Veldhuizen has authored 24 papers receiving a total of 784 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Radiology, Nuclear Medicine and Imaging, 8 papers in Artificial Intelligence and 7 papers in Oncology. Recurrent topics in Gregory Patrick Veldhuizen's work include Radiomics and Machine Learning in Medical Imaging (8 papers), Colorectal Cancer Screening and Detection (7 papers) and Hormonal Regulation and Hypertension (7 papers). Gregory Patrick Veldhuizen is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (8 papers), Colorectal Cancer Screening and Detection (7 papers) and Hormonal Regulation and Hypertension (7 papers). Gregory Patrick Veldhuizen collaborates with scholars based in Germany, Netherlands and United Kingdom. Gregory Patrick Veldhuizen's co-authors include Jakob Nikolas Kather, Fiona R. Kolbinger, Narmin Ghaffari Laleh, Hannah Sophie Muti, Chiara Maria Lavinia Löffler, Sophia J. Wagner, Zunamys I. Carrero, Jan‐Niklas Eckardt, Michaela Unger and Jan Clusmann and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and European Journal of Cancer.

In The Last Decade

Gregory Patrick Veldhuizen

19 papers receiving 763 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.

The future landscape of large language models in medicine

2023 472 citations Jan Clusmann, Fiona R. Kolbinger et al. SHILAP Revista de lepidopterología profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Gregory Patrick Veldhuizen Germany	11	350	349	292	69	58	24	784
Hannah Sophie Muti Germany	9	297 0.8×	267 0.8×	223 0.8×	73 1.1×	30 0.5×	15	647
Jan‐Niklas Eckardt Germany	9	370 1.1×	331 0.9×	234 0.8×	39 0.6×	24 0.4×	21	810
Judy J. Wang United States	6	187 0.5×	386 1.1×	278 1.0×	83 1.2×	19 0.3×	13	779
Luke Gompels United Kingdom	10	290 0.8×	180 0.5×	180 0.6×	66 1.0×	98 1.7×	13	1.0k
Vera Sorin Israel	17	544 1.6×	462 1.3×	564 1.9×	85 1.2×	35 0.6×	59	1.2k
Jonathan Montomoli Italy	14	554 1.6×	323 0.9×	273 0.9×	57 0.8×	155 2.7×	36	1.1k
Thushika Mahendiran United Kingdom	1	447 1.3×	367 1.1×	470 1.6×	76 1.1×	66 1.1×	2	1.0k
Mohith Shamdas United Kingdom	6	452 1.3×	368 1.1×	478 1.6×	78 1.1×	69 1.2×	10	1.1k
Michaela Unger Germany	4	291 0.8×	237 0.7×	173 0.6×	31 0.4×	20 0.3×	5	556
Aditya U. Kale United Kingdom	6	459 1.3×	369 1.1×	515 1.8×	76 1.1×	70 1.2×	20	1.1k

Countries citing papers authored by Gregory Patrick Veldhuizen

Since Specialization

Citations

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

Fields of papers citing papers by Gregory Patrick Veldhuizen

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gregory Patrick Veldhuizen. 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 Gregory Patrick Veldhuizen. The network helps show where Gregory Patrick Veldhuizen may publish in the future.

Co-authorship network of co-authors of Gregory Patrick Veldhuizen

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

All Works

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20 of 20 papers shown

Çifçi, Didem, Gregory Patrick Veldhuizen, Wan-Jung Tsai, et al.. (2025). Deep learning predicts microsatellite instability status in colorectal carcinoma in an ethnically heterogeneous population in South Africa. Journal of Clinical Pathology. 79(1). 50–56.

Veldhuizen, Gregory Patrick, Didem Çifçi, Marko van Treeck, et al.. (2025). Deep learning can predict cardiovascular events from liver imaging. JHEP Reports. 7(8). 101427–101427.

Kolbinger, Fiona R., Gregory Patrick Veldhuizen, Jiefu Zhu, Daniel Truhn, & Jakob Nikolas Kather. (2024). Reporting guidelines in medical artificial intelligence: a systematic review and meta-analysis. SHILAP Revista de lepidopterología. 4(1). 71–71. 47 indexed citations

Veldhuizen, Gregory Patrick, Oliver Lester Saldanha, Jonas Rosendahl, et al.. (2024). Deep Learning-Based Detection of Malignant Bile Duct Stenosis in Fluoroscopy Images of Endoscopic Retrograde Cholangiopancreatography. Digestion. 106(4). 287–302.

Clusmann, Jan, Fiona R. Kolbinger, Hannah Sophie Muti, et al.. (2024). Die kommende Entwicklung großer Sprachmodelle in der Medizin. 11(1). 3–10.

Niehues, Jan, Gustav Müller‐Franzes, Sophia J. Wagner, et al.. (2024). Using histopathology latent diffusion models as privacy-preserving dataset augmenters improves downstream classification performance. Computers in Biology and Medicine. 175. 108410–108410. 5 indexed citations

Clusmann, Jan, Fiona R. Kolbinger, Hannah Sophie Muti, et al.. (2023). The future landscape of large language models in medicine. SHILAP Revista de lepidopterología. 3(1). 141–141. 472 indexed citations breakdown →

Veldhuizen, Gregory Patrick, Christoph Röcken, Hans‐Michael Behrens, et al.. (2023). Deep learning-based subtyping of gastric cancer histology predicts clinical outcome: a multi-institutional retrospective study. Gastric Cancer. 26(5). 708–720. 13 indexed citations

Saldanha, Oliver Lester, Chiara Maria Lavinia Loeffler, Jan Niehues, et al.. (2023). Self-supervised attention-based deep learning for pan-cancer mutation prediction from histopathology. npj Precision Oncology. 7(1). 35–35. 41 indexed citations

10.

Niehues, Jan, Philip Quirke, Nicholas P. West, et al.. (2023). Generalizable biomarker prediction from cancer pathology slides with self-supervised deep learning: A retrospective multi-centric study. Cell Reports Medicine. 4(4). 100980–100980. 46 indexed citations

11.

Hewitt, Katherine, Chiara Maria Lavinia Löffler, Hannah Sophie Muti, et al.. (2023). Direct image to subtype prediction for brain tumors using deep learning. Neuro-Oncology Advances. 5(1). vdad139–vdad139. 13 indexed citations

12.

Veldhuizen, Gregory Patrick, et al.. (2023). The effect of age, sex and BMI on the aldosterone-to-renin ratio in essential hypertensive individuals. Journal of Hypertension. 41(4). 618–623. 5 indexed citations

13.

Niehues, Jan, Marko van Treeck, Chiara Maria Lavinia Loeffler, et al.. (2023). Prediction models for hormone receptor status in female breast cancer do not extend to males: further evidence of sex-based disparity in breast cancer. npj Breast Cancer. 9(1). 91–91. 3 indexed citations

14.

Röcken, Christoph, Hans‐Michael Behrens, Chiara Maria Lavinia Löffler, et al.. (2023). Deep learning trained on lymph node status predicts outcome from gastric cancer histopathology: a retrospective multicentric study. European Journal of Cancer. 194. 113335–113335. 13 indexed citations

15.

Laleh, Narmin Ghaffari, Daniel Truhn, Gregory Patrick Veldhuizen, et al.. (2022). Adversarial attacks and adversarial robustness in computational pathology. Nature Communications. 13(1). 5711–5711. 53 indexed citations

16.

Veldhuizen, Gregory Patrick, et al.. (2022). Variability of aldosterone, renin and the aldosterone-to-renin ratio in hypertensive patients without primary aldosteronism. Journal of Hypertension. 40(11). 2256–2262. 3 indexed citations

17.

Saldanha, Oliver Lester, Hannah Sophie Muti, Heike I. Grabsch, et al.. (2022). Direct prediction of genetic aberrations from pathology images in gastric cancer with swarm learning. Gastric Cancer. 26(2). 264–274. 24 indexed citations

18.

Veldhuizen, Gregory Patrick, et al.. (2021). The Effects of Verapamil, Hydralazine, and Doxazosin on Renin, Aldosterone, and the Ratio Thereof. Cardiovascular Drugs and Therapy. 37(2). 283–289. 5 indexed citations

19.

Veldhuizen, Gregory Patrick, et al.. (2020). Confounders of the aldosterone‐to‐renin ratio when used as a screening test in hypertensive patients: A critical analysis of the literature. Journal of Clinical Hypertension. 23(2). 201–207. 9 indexed citations

20.

Veldhuizen, Gregory Patrick, et al.. (2019). THE INFLUENCE OF CONFOUNDERS ON THE ALDOSTERONE-TO-RENIN RATIO AS A SCREENING TEST FOR PRIMARY HYPERALDOSTERONISM. A SYSTEMATIC ANALYSIS OF THE LITERATURE. Journal of Hypertension. 37. e30–e30.

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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