20152020

Research output per year

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Fingerprint Dive into the research topics where P.A.N. Bosman is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

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Research Output

Automatic generation of three-dimensional dose reconstruction data for two-dimensional radiotherapy plans for historically treated patients

Wang, Z., Virgolin, M., Bosman, P. A. N., Crama, K. F., Balgobind, B. V., Bel, A. & Alderliesten, T., 1 Jan 2020, In : Journal of Medical Imaging. 7, 1, 015001.

Research output: Contribution to journalArticleScientificpeer-review

  • Machine learning for automatic construction of pediatric abdominal phantoms for radiation dose reconstruction

    Virgolin, M., Wang, Z., Alderliesten, T. & Bosman, P. A. N., 2020, Medical Imaging 2020: Imaging Informatics for Healthcare, Research, and Applications. Chen, P-H. & Deserno, T. M. (eds.). SPIE, Vol. 11318. 7 p. 1131815

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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    On explaining machine learning models by evolving crucial and compact features

    Virgolin, M., Alderliesten, T. & Bosman, P. A. N., 2020, In : Swarm and Evolutionary Computation. 53, p. 1-13 13 p., 100640.

    Research output: Contribution to journalArticleScientificpeer-review

  • Automatic radiotherapy plan emulation for 3D dose reconstruction to enable big data analysis for historically treated patients

    Wang, Z., Virgolin, M., Bosman, P. A. N., Balgobind, B. V., Bel, A. & Alderliesten, T., 2019, Medical Imaging 2019: Imaging Informatics for Healthcare, Research, and Applications. Bak, P. R. & Chen, P-H. (eds.). SPIE, Vol. 10954. p. 1-9 9 p. 109540V. (Proceedings of SPIE).

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

  • 1 Citation (Scopus)

    Convolutional neural network surrogate-assisted GOMEA

    Dushatskiy, A., Mendrik, A. M., Alderliesten, T. & Bosman, P. A. N., 2019, GECCO 2019 : Proceedings of the 2019 Genetic and Evolutionary Computation Conference. New York: Association for Computing Machinery (ACM), p. 753-761 9 p.

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review