Tanja Alderliesten

Virgolin, M, Alderliesten, T, & Bosman, P.A.N. (2020). On explaining machine learning models by evolving crucial and compact features. Swarm and Evolutionary Computation, 53. doi:10.1016/j.swevo.2019.100640

Luong, N.H, Alderliesten, T, Pieters, B.R, Bel, A, Niatsetski, Y, & Bosman, P.A.N. (2019). Fast and insightful bi-objective optimization for prostate cancer treatment planning with high-dose-rate brachytherapy. Applied Soft Computing, 84. doi:10.1016/j.asoc.2019.105681

Dushatskiy, A, Alderliesten, T, Mendrik, A, & Bosman, P.A.N. (2019). Convolutional neural network surrogate-assisted GOMEA. In Proceedings of the 2019 Genetic and Evolutionary Computation Conference (pp. 753–761). doi:10.1145/3321707.3321760

Maree, S.C, Alderliesten, T, & Bosman, P.A.N. (2019). Real-valued evolutionary multi-modal multi-objective optimization by hill-valley clustering. In Proceedings of the 2019 Genetic and Evolutionary Computation Conference (pp. 568–576). doi:10.1145/3321707.3321759

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

Bouter, P.A, Alderliesten, T, Pieters, B.R, Bel, A, Niatsetski, Y, & Bosman, P.A.N. (2019). GPU-accelerated bi-objective treatment planning for prostate high-dose-rate brachytherapy. Medical Physics. doi:10.1002/mp.13681

Pirpinia, K, Bosman, P.A.N, Sonke, J.-J, van Herk, M, & Alderliesten, T. (2019). Evolutionary machine learning for multi-objective class solutions in medical deformable image registration. Special Issue: Evolutionary Algorithms in Health Technologies, 12(5). doi:10.3390/a12050099

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

van der Meer, M.C, Bosman, P.A.N, Pieters, B.R, Niatsetski, Y, van Wieringen, N, Alderliesten, T, & Bel, A. (2019). Sensitivity of dose-volume indices to computation settings in high-dose-rate prostate brachytherapy treatment plan evaluation. Journal of Applied Clinical Medical Physics, 20(4), 66–74. doi:10.1002/acm2.12563

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