Marco Virgolin

Virgolin, M, Alderliesten, T, & Bosman, P.A.N. (2019). Linear scaling with and within semantic backpropagation-based genetic programming for symbolic regression. In Proceedings of the 2019 Genetic and Evolutionary Computation Conference (pp. 1084–1092). doi:10.1145/3321707.3321758

Wang, Z, Balgobind, B.V, Virgolin, M, Dijk, van, I.W.E.M, Wiersma, J, Ronckers, C.M, … Alderliesten, T. (2019). How do patient characteristics and anatomical features correlate to accuracy of organ dose reconstruction for Wilms' tumor radiation treatment plans when using a surrogate patient's CT scan?. Journal of Radiological Protection, 39, 598–619. doi:10.1088/1361-6498/ab1796

Wang, Z, Virgolin, M, Bosman, P.A.N, Balgobind, B.V, Bel, A, & Alderliesten, T. (2019). Automatic radiotherapy plan emulation for 3D dose reconstruction to enable big data analysis for historically treated patients. In Medical Imaging 2019: Imaging Informatics for Healthcare, Research, and Applications. doi:10.1117/12.2512758

Medvet, E, Virgolin, M, Castelli, M, Bosman, P.A.N, Gonçalves, I, & Tušar, T. (2018). Unveiling evolutionary algorithm representation with DU maps. Genetic Programming and Evolvable Machines - Topical Collection: Genetic Programming, Evolutionary Computation and Visualization, 1–39. doi:10.1007/s10710-018-9332-5

Virgolin, M, Alderliesten, T, Bel, A, Witteveen, C, & Bosman, P.A.N. (2018). Symbolic regression and feature construction with GP-GOMEA applied to radiotherapy dose reconstruction of childhood cancer survivors. In GECCO 2018 - Proceedings of the 2018 Genetic and Evolutionary Computation Conference (pp. 1395–1402). doi:10.1145/3205455.3205604

Virgolin, M, Dijk, van, I.W.E.M, Wiersma, J, Ronckers, C.M, Witteveen, C, Bel, A, … Bosman, P.A.N. (2018). On the feasibility of automatically selecting similar patients in highly individualized radiotherapy dose reconstruction for historic data of pediatric cancer survivors. Medical Physics. doi:10.1002/mp.12802

Virgolin, M, Witteveen, C, Alderliesten, T, & Bosman, P.A.N. (2017). Scalable genetic programming by gene-pool optimal mixing and input-space entropy-based building-block learning. In GECCO 2017 - Proceedings of the 2017 Genetic and Evolutionary Computation Conference (pp. 1041–1048). doi:10.1145/3071178.3071287

Virgolin, M, Dijk, van, I.W.E.M, Wiersma, J, Ronckers, C.M, Witteveen, C, Rasch, C.R.N, … Bosman, P.A.N. (2016). Learning to Associate Distances with Historical Patient Data to Enable Fine-grained Studying of Late Adverse Effects of Paediatric Radiotherapy: Data, Methodology, and First Results. In Proceedings of the 18th International Conference on the use of Computers in Radiation Therapy.