- Genetic and Evolutionary Computation: Medical Applications / Edition 1
- Evostar 2018
- IEEE Congress on Evolutionary Computation
- 21st International Conference on the Applications of Evolutionary Computation
This Book have some digital formats such us :paperbook, ebook, kindle, epub, fb2 and another formats. List of genetic algorithm applications The objective of this special session is the development and use of these computational intelligence methods in healthcare domain. Howard, Andy M. Tyrrell, and Crispin Cooper. Who Was Sylvia! Happy Hoppy Toad.
List of genetic algorithm applications - Wikipedia. List of genetic algorithm applications. Undetected country. NO YES. Genetic and Evolutionary Computation: Medical Applications. Account Options. Zeitzeugen: Max Mannheimer German Edition? Evostar Multiobjective Scheduling by Genetic Algorithms. Languages Add links.
Genetic and Evolutionary Computation: Medical Applications / Edition 1
Search books. Fast and insightful bi-objective optimization for prostate cancer treatment planning with high-dose-rate brachytherapy. In Applied Soft Computing. Bouter, T. In Medical Physics. Bosman , B.
Pieters, Y. Niatsetski, T. Alderliesten, and A. Robust HDR prostate brachytherapy planning accounting for organ reconstruction settings. Pirpinia, P. Bosman , J. Sonke, M. In Algorithms. Bi-objective optimization of dosimetric indices for HDR prostate brachytherapy within 30 seconds. Wang, B. Balgobind, M. Virgolin, I. Wiersma, C. Ronckers, P. Bosman , A. Bel, and T. In Journal of Radiological Protection.
Maree, T. Alderliesten, and P. Virgolin, T. Dushatskiy, A. Mendrik, T. Meulman, and P.
Hart et al. Bouter, B. Alderliesten, P. Bosman , and A. Maree, N. Luong, E. Kooreman, N. Bel, K. Hinnen, H. Westerveld, B. Pieters, P. Bosman , and T. Evaluation of bi-objective treatment planning for high-dose-rate prostatebrachytherapy — A retrospective observer study.
In Brachytherapy. Evolutionary multi-objective meta-optimization of deformation and tissue removal parameters improves the performance of deformable image registration of pre- and post-surgery images. Wang, M. Virgolin, P. Balgobind, A. Automatic radiotherapy plan emulation for 3D dose reconstruction to enable big data analysis for historically treated patients.
Niatsetski, N. Sensitivity of dose-volume indices to computation settings in high-dose-rate prostate brachytherapy treatment plan evaluation. Evaluation of bi-objective treatment planning for high-dose-rate prostate brachytherapy -- A retrospective observer study. Bosman , C. Loo, N. Russell, M. Simplex-based navigation tool for a posteriori selection of the preferred deformable image registration outcome from a set of trade-off solutions obtained with multi-objective optimization for the case of breast MRI.
In Journal of Medical Imaging. Medvet, M. Virgolin, M. Castelli, P. Bosman , I. Unveiling evolutionary algorithm representation with DU maps. In Genetic Programming and Evolvable Machines. Aalvanger, H. Luong, P. Bosman and D.
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Witteveen, and P. Bel, and P. Orphanou, D. Thierens, and P. Alderliesten, D. Wang, I. Ronckers, F. Oldenburger, B. Balgobind, P. Are age and gender suitable matching criteria in organ dose reconstruction using surrogate childhood cancer patients' CT scans? Luong, H.
In Swarm and Evolutionary Computation. Fast and insightful bi-objective HDR prostate brachytherapy planning. Sensitivity of dose-volume indices to organ reconstruction settings in HDR prostate brachytherapy. Maree, E. Luong, N. Bel, E.
Rodenburg, K. Hinnen, G. Better plans and easy plan selection via bi-objective optimization for HDR prostate brachytherapy. Ronckers, C. Witteveen, A. Bel, T. On the feasibility of automatically selecting similar patients in highly individualized radiotherapy dose reconstruction for historic data of pediatric cancer survivors. Bosman , M. Grond, and H. Lee and Z.
IEEE Congress on Evolutionary Computation
Bosman and M. In Soft Computing , 22 4 , pages , Loo, G. Winter-Warnars, N. Janssen, A. Scholten, J. In Physics in Medicine and Biology 62 14 , pages , Sadowski, D. Rodrigues, P. Bauer, and P. Rodrigues, C. Restrepo, G. Katsouris, R. Pinto, M. Soleimanzadeh, P. Bosman , and P. In Energies 9 3 , , Rodrigues, R.
In Energy Conversion and Management 89 , pages , Grahl, and D. In Evolutionary Computation 21 3 , pages , Bosman and J. In European Journal of Operational Research 3 , pages , Bosman , and W.
21st International Conference on the Applications of Evolutionary Computation
In International Journal of Approximate Reasoning , 31 3 , pages , Bouter, N. Luong, C. Witteveen, T. The multi-objective real-valued gene-pool optimal mixing evolutionary algorithm. Ochoa et al. Alderliesten, C. Exploiting linkage information in real-valued optimization with the real-valued gene-pool optimal mixing evolutionary algorithm. Scalable genetic programming by gene-pool optimal mixing and input-space entropy-based building block learning. Niching an estimation-of-distribution algorithm by hierarchical Gaussian mixture learning. Sadowski, M. Thierens, R. Niatsetski, A.
Exploring trade-offs between target coverage, healthy tissue sparing, and the placement of catheters in HDR brachytherapy for prostate cancer using a novel multi-objective model-based mixed-integer evolutionary algorithm. A novel model-based evolutionary algorithm for multi-objective deformable image registration with content mismatch and large deformations: benchmarking efficiency and quality.
Styner and E. Handl et al. Bosman , N. Luong, and D. Friedrich et al. Sadowski, P. Bosman , and D.