Researcher

Dekker, A.L.A.J.

Persoonlijk hoogleraar

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  1. 2018
  2. Published
  3. Published
  4. Published
    El Naqa, I., Ruan, D., Valdes, G., Dekker, A., McNutt, T., Ge, Y., ... Ten Haken, R. (2018). Machine learning and modeling: Data, validation, communication challenges. Medical Physics, 45(10), E834-E840. DOI: 10.1002/mp.12811
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    Mayo, C. S., Phillips, M., McNutt, T. R., Palta, J., Dekker, A., Miller, R. C., ... Lawrence, T. S. (2018). Treatment data and technical process challenges for practical big data efforts in radiation oncology. Medical Physics, 45(10), E793-E810. DOI: 10.1002/mp.13114
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  13. 2017
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    Alitto, A. R., Gatta, R., Vanneste, B. G. L., Vallati, M., Meldolesi, E., Damiani, A., ... Mantini, G. (2017). PRODIGE: PRediction models in prOstate cancer for personalized meDIcine challenGE. Future Oncology, 13(24), 2171-2181. DOI: 10.2217/fon-2017-0142
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  23. 2016
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    Dekker, A. L. A. J. (2016). Leren van andermans data. Maastricht: Maastricht University.
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    Hu, Q., Huang, Z., Ten Teije, A., Van Harmelen, F., Marshall, M. S., & Dekker, A. (2016). A topic-centric approach to detecting new evidences for evidence-based medical guidelines. In HEALTHINF 2016: 9th International Conference on Health Informatics, Proceedings; Part of 9th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2016 (pp. 282-289). SCITEPRESS.
  29. Published
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    Meldolesi, E., van Soest, J., Damiani, A., Dekker, A., Alitto, A. R., Campitelli, M., ... Valentini, V. (2016). Standardized data collection to build prediction models in oncology: a prototype for rectal cancer. Future Oncology, 12(1), 119-36. DOI: 10.2217/fon.15.295
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  33. 2015
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    Shen, L., van Soest, J., Wang, J., Yu, J., Hu, W., Gong, Y. U. T., ... Zhang, Z. (2015). Validation of a rectal cancer outcome prediction model with a cohort of Chinese patients. Oncotarget, 6(35), 38327-38335. DOI: 10.18632/oncotarget.5195
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    Grove, O., Berglund, A. E., Schabath, M. B., Aerts, H. J. W. L., Dekker, A., Wang, H., ... Gillies, R. J. (2015). Quantitative Computed Tomographic Descriptors Associate Tumor Shape Complexity and Intratumor Heterogeneity with Prognosis in Lung Adenocarcinoma. PLOS ONE, 10(3), [e0118261]. DOI: 10.1371/journal.pone.0118261
  37. Published
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    Meldolesi, E., van Soest, J., Dinapoli, N., Dekker, A., Damiani, A., Gambacorta, M. A., & Valentini, V. (2015). Medicine is a science of uncertainty and an art of probability (Sir W. Osler). Radiotherapy and Oncology, 114(1), 132-134. DOI: 10.1016/j.radonc.2014.12.013
  40. 2014
  41. Published
    Skripcak, T., Belka, C., Bosch, W., Brink, C., Brunner, T., Budach, V., ... Baumann, M. (2014). Creating a data exchange strategy for radiotherapy research: Towards federated databases and anonymised public datasets. Radiotherapy and Oncology, 113(3), 303-309. DOI: 10.1016/j.radonc.2014.10.001
  42. Published
  43. Published
    Dekker, A., Vinod, S., Holloway, L., Oberije, C., George, A., Goozee, G., ... Thwaites, D. (2014). Rapid learning in practice: a lung cancer survival decision support system in routine patient care data. Radiotherapy and Oncology, 113(1), 47-53. DOI: 10.1016/j.radonc.2014.08.013
  44. Published
    Rosenstein, B. S., West, C. M., Bentzen, S. M., Alsner, J., Andreassen, C. N., Azria, D., ... Zenhausern, F. (2014). Radiogenomics: Radiobiology Enters the Era of Big Data and Team Science. International Journal of Radiation Oncology Biology Physics, 89(4), 709-713. DOI: 10.1016/j.ijrobp.2014.03.009
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    Aerts, H. J. W. L., Velazquez, E. R., Leijenaar, R. T. H., Parmar, C., Grossmann, P., Cavalho, S., ... Lambin, P. (2014). Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach. Nature Communications, 5, [4006]. DOI: 10.1038/ncomms5006
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    Ibrahim, A., Bucur, A., Dekker, A., Marshall, M. S., Perez-Rey, D., Alonso-Calvo, R., ... Mehta, K. (2014). Analysis of the Suitability of Existing Medical Ontologies for Building a Scalable Semantic Interoperability Solution Supporting Multi-site Collaboration in Oncology. In Proceedings - IEEE 14th International Conference on Bioinformatics and Bioengineering, BIBE 2014 (pp. 204-211). (Proceedings - IEEE 14th International Conference on Bioinformatics and Bioengineering, BIBE 2014). IEEE. DOI: 10.1109/BIBE.2014.12
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    Kerns, S. L., West, C. M. L., Andreassen, C. N., Barnett, G. C., Bentzen, S. M., Burnet, N. G., ... Rosenstein, B. S. (2014). Radiogenomics: the search for genetic predictors of radiotherapy response. Future Oncology, 10(15), 2391-2406. DOI: 10.2217/fon.14.173
  53. Published
    Van Soest, J., Lustberg, T., Grittner, D., Marshall, M. S., Persoon, L., Nijsten, B., ... Dekker, A. (2014). Towards a semantic PACS: Using Semantic Web technology to represent imaging data. Studies in health technology and informatics, 205, 166-70. DOI: 10.3233/978-1-61499-432-9-166
  54. Published
    Meldolesi, E., Van Soest, J., Alitto, A. R., Autorino, R., Dinapoli, N., Dekker, A., ... Valentini, V. (2014). VATE: VAlidation of high TEchnology based on large database analysis by learning machine. Colorectal Cancer, 3(5), 435-450. DOI: 10.2217/crc.14.34
  55. 2013
  56. Published
    Latifi, K., Huang, T-C., Feygelman, V., Budzevich, M. M., Moros, E. G., Dilling, T. J., ... Zhang, G. G. (2013). Effects of quantum noise in 4D-CT on deformable image registration and derived ventilation data. Physics in Medicine and Biology, 7661-7672. DOI: 10.1088/0031-9155/58/21/7661
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