André Dekker

34.9k total citations · 7 hit papers
329 papers, 23.4k citations indexed

About

André Dekker is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Radiation. According to data from OpenAlex, André Dekker has authored 329 papers receiving a total of 23.4k indexed citations (citations by other indexed papers that have themselves been cited), including 199 papers in Radiology, Nuclear Medicine and Imaging, 115 papers in Pulmonary and Respiratory Medicine and 77 papers in Radiation. Recurrent topics in André Dekker's work include Radiomics and Machine Learning in Medical Imaging (151 papers), Lung Cancer Diagnosis and Treatment (80 papers) and Advanced Radiotherapy Techniques (76 papers). André Dekker is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (151 papers), Lung Cancer Diagnosis and Treatment (80 papers) and Advanced Radiotherapy Techniques (76 papers). André Dekker collaborates with scholars based in Netherlands, United States and Italy. André Dekker's co-authors include Philippe Lambin, Robert J. Gillies, Hugo J.W.L. Aerts, Ralph T. H. Leijenaar, Sara Carvalho, Ruud G.P.M. van Stiphout, Catharina M.L. Zegers, Patrick V. Granton, Ronald Boellard and Wouter van Elmpt and has published in prestigious journals such as Nature Medicine, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

André Dekker

301 papers receiving 23.2k citations

Hit Papers

Radiomics: Extracting mor... 2012 2026 2016 2021 2012 2017 2014 2012 2020 1000 2.0k 3.0k 4.0k
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.

  1. Radiomics: Extracting more information from medical images using advanced feature analysis
    2012 4.1k citations Philippe Lambin, Ralph T. H. Leijenaar et al. European Journal of Cancer profile →
  2. Radiomics: the bridge between medical imaging and personalized medicine
    2017 3.7k citations Philippe Lambin, Ralph T. H. Leijenaar et al. profile →
  3. Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach
    2014 3.6k citations Hugo J.W.L. Aerts, Ralph T. H. Leijenaar et al. profile →
  4. Radiomics: the process and the challenges
    2012 1.7k citations Hugo J.W.L. Aerts, André Dekker et al. profile →
  5. Characterisation and classification of oligometastatic disease: a European Society for Radiotherapy and Oncology and European Organisation for Research and Treatment of Cancer consensus recommendation
    2020 631 citations Laurence Collette, André Dekker et al. profile →
  6. Repeatability and Reproducibility of Radiomic Features: A Systematic Review
    2018 588 citations Alberto Traverso, Leonard Wee et al. International Journal of Radiation Oncology*Biology*Physics profile →
  7. Clinical evaluation of atlas and deep learning based automatic contouring for lung cancer
    2017 263 citations Tim Lustberg, Johan van Soest et al. Radiotherapy and Oncology profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
André Dekker 18.8k 8.6k 5.5k 3.8k 3.4k 329 23.4k
Hugo J.W.L. Aerts 27.2k 1.4× 11.4k 1.3× 7.6k 1.4× 5.3k 1.4× 5.8k 1.7× 268 33.1k
Philippe Lambin 29.7k 1.6× 17.4k 2.0× 8.4k 1.5× 9.0k 2.4× 4.6k 1.3× 720 46.6k
Ralph T. H. Leijenaar 15.2k 0.8× 6.1k 0.7× 4.3k 0.8× 3.0k 0.8× 2.6k 0.8× 84 16.8k
Issam El Naqa 8.3k 0.4× 6.0k 0.7× 2.4k 0.4× 1.5k 0.4× 1.8k 0.5× 349 14.9k
Chintan Parmar 13.5k 0.7× 5.4k 0.6× 3.9k 0.7× 2.4k 0.6× 3.0k 0.9× 36 15.8k
Wouter van Elmpt 8.4k 0.4× 4.2k 0.5× 2.5k 0.5× 1.3k 0.3× 977 0.3× 193 10.2k
Joseph O. Deasy 9.8k 0.5× 8.6k 1.0× 1.9k 0.4× 1.7k 0.4× 957 0.3× 453 17.2k
Lawrence H. Schwartz 16.5k 0.9× 20.6k 2.4× 3.0k 0.5× 21.2k 5.6× 2.1k 0.6× 395 52.0k
Richard L. Wahl 20.0k 1.1× 8.5k 1.0× 2.8k 0.5× 6.6k 1.7× 370 0.1× 584 34.3k
Clare M. Tempany 8.0k 0.4× 8.1k 0.9× 4.2k 0.8× 818 0.2× 1.1k 0.3× 273 18.7k

Countries citing papers authored by André Dekker

Since Specialization
Citations

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

Fields of papers citing papers by André Dekker

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by André Dekker. 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 André Dekker. The network helps show where André Dekker may publish in the future.

Co-authorship network of co-authors of André Dekker

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

All Works

20 of 20 papers shown
1.
Gupta, Prashant, et al.. (2024). Development and validation of multicentre study on novel Artificial Intelligence-based Cardiovascular Risk Score (AICVD). Family Medicine and Community Health. 12(Suppl 1). e002340–e002340. 4 indexed citations
2.
3.
Bajardi, Paolo, Guido Bologna, Francesco Bonchi, et al.. (2024). PRE-ACT: Prediction of Radiotherapy side Effects using explainable AI for patient Communication and Treatment modification. Journal of Cancer Policy. 43. 100537–100537.
4.
Jaarsma, Eva A., Esther E. Bron, Frank J. Wolters, et al.. (2024). Data harmonization and federated learning for multi-cohort dementia research using the OMOP common data model: A Netherlands consortium of dementia cohorts case study. Journal of Biomedical Informatics. 155. 104661–104661. 8 indexed citations
5.
Field, Matthew, Shalini Vinod, Geoff P. Delaney, et al.. (2024). Federated Learning Survival Model and Potential Radiotherapy Decision Support Impact Assessment for Non–small Cell Lung Cancer Using Real-World Data. Clinical Oncology. 36(7). e197–e208. 4 indexed citations
6.
Jha, Ashish Kumar, Alberto Traverso, Nilendu Purandare, et al.. (2023). Emerging role of quantitative imaging (radiomics) and artificial intelligence in precision oncology. SHILAP Revista de lepidopterología. 4(4). 569–582. 17 indexed citations
7.
Zhang, Zhen, Anne‐Marie C. Dingemans, Joachim G.J.V. Aerts, et al.. (2023). Computed tomography-based radiomics for the differential diagnosis of pneumonitis in stage IV non-small cell lung cancer patients treated with immune checkpoint inhibitors. European Journal of Cancer. 183. 142–151. 16 indexed citations
8.
9.
Hemelrijck, Mieke Van, Jan Bogaerts, Christopher M. Booth, et al.. (2023). Defining the role of real-world data in cancer clinical research: The position of the European Organisation for Research and Treatment of Cancer. European Journal of Cancer. 186. 52–61. 38 indexed citations
10.
Wee, Leonard, Patricia Sánchez González, Enrique J. Gómez Aguilera, et al.. (2021). Deep Learning Automated Segmentation for Muscle and Adipose Tissue from Abdominal Computed Tomography in Polytrauma Patients. Sensors. 21(6). 2083–2083. 32 indexed citations
11.
Kalendralis, Petros, Richard Canters, Alan M. Kalet, et al.. (2021). External Validation of a Bayesian Network for Error Detection in Radiotherapy Plans. IEEE Transactions on Radiation and Plasma Medical Sciences. 6(2). 200–206. 5 indexed citations
12.
Zegers, Catharina M.L., Alberto Traverso, Daniëlle B. P. Eekers, et al.. (2021). Current applications of deep-learning in neuro-oncological MRI. Physica Medica. 83. 161–173. 25 indexed citations
13.
Zhai, Tian‐Tian, Frederik Wesseling, Johannes A. Langendijk, et al.. (2020). External validation of nodal failure prediction models including radiomics in head and neck cancer. Oral Oncology. 112. 105083–105083. 20 indexed citations
14.
Gambacorta, Maria Antonietta, Carlotta Masciocchi, Giuditta Chiloiro, et al.. (2020). Timing to achieve the highest rate of pCR after preoperative radiochemotherapy in rectal cancer: a pooled analysis of 3085 patients from 7 randomized trials. Radiotherapy and Oncology. 154. 154–160. 49 indexed citations
15.
Boukerroui, Djamal, Devis Peressutti, Johan van Soest, et al.. (2019). An Evaluation of Atlas Selection Methods for Atlas-Based Automatic Segmentation in Radiotherapy Treatment Planning. IEEE Transactions on Medical Imaging. 38(11). 2654–2664. 25 indexed citations
16.
Dekker, André, et al.. (2019). Big data for better cancer care. British Journal of Hospital Medicine. 80(6). 304–305. 1 indexed citations
17.
Dekker, André, Michel Dumontier, & Pieter Kubben. (2018). Fundamentals of Clinical Data Science. Research Publications (Maastricht University). 132 indexed citations
18.
Boukerroui, Djamal, Devis Peressutti, Johan van Soest, et al.. (2018). Can Atlas-Based Auto-Segmentation Ever Be Perfect? Insights From Extreme Value Theory. IEEE Transactions on Medical Imaging. 38(1). 99–106. 22 indexed citations
19.
Dinapoli, N., Johan van Soest, Carlotta Masciocchi, et al.. (2016). Radiomics in Magnetic Resonance Imaging for Prognosis in Patients With Rectal Cancer: An Independent External Validation. International Journal of Radiation Oncology*Biology*Physics. 96(2). E180–E181. 3 indexed citations
20.
Lambin, Philippe, Ralph T. H. Leijenaar, Sara Carvalho, et al.. (2012). Radiomics: Extracting more information from medical images using advanced feature analysis. European Journal of Cancer. 48(4). 441–446. 4110 indexed citations breakdown →

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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