Zobrazeno 1 - 10
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pro vyhledávání: '"Alderliesten T"'
Many real-world problems have expensive-to-compute fitness functions and are multi-objective in nature. Surrogate-assisted evolutionary algorithms are often used to tackle such problems. Despite this, literature about analysing the fitness landscapes
Externí odkaz:
http://arxiv.org/abs/2404.06557
Volume measurement of a paraganglioma (a rare neuroendocrine tumor that typically forms along major blood vessels and nerve pathways in the head and neck region) is crucial for monitoring and modeling tumor growth in the long term. However, in clinic
Externí odkaz:
http://arxiv.org/abs/2404.07952
Paragangliomas are rare, primarily slow-growing tumors for which the underlying growth pattern is unknown. Therefore, determining the best care for a patient is hard. Currently, if no significant tumor growth is observed, treatment is often delayed,
Externí odkaz:
http://arxiv.org/abs/2402.12510
Explainable artificial intelligence (XAI) is an important and rapidly expanding research topic. The goal of XAI is to gain trust in a machine learning (ML) model through clear insights into how the model arrives at its predictions. Genetic programmin
Externí odkaz:
http://arxiv.org/abs/2203.13347
In model-based evolutionary algorithms (EAs), the underlying search distribution is adapted to the problem at hand, for example based on dependencies between decision variables. Hill-valley clustering is an adaptive niching method in which a set of s
Externí odkaz:
http://arxiv.org/abs/2010.14998
The aim of bi-objective optimization is to obtain an approximation set of (near) Pareto optimal solutions. A decision maker then navigates this set to select a final desired solution, often using a visualization of the approximation front. The front
Externí odkaz:
http://arxiv.org/abs/2006.06449
Domination-based multi-objective (MO) evolutionary algorithms (EAs) are today arguably the most frequently used type of MOEA. These methods however stagnate when the majority of the population becomes non-dominated, preventing convergence to the Pare
Externí odkaz:
http://arxiv.org/abs/2004.05068
Surrogate-free machine learning-based organ dose reconstruction for pediatric abdominal radiotherapy
Autor:
Virgolin, M., Wang, Z., Balgobind, B. V., van Dijk, I. W. E. M., Wiersma, J., Kroon, P. S., Janssens, G. O., van Herk, M., Hodgson, D. C., Zaletel, L. Zadravec, Rasch, C. R. N., Bel, A., Bosman, P. A. N., Alderliesten, T.
Publikováno v:
Physics in Medicine & Biology. 2020 Dec 8;65(24):245021
To study radiotherapy-related adverse effects, detailed dose information (3D distribution) is needed for accurate dose-effect modeling. For childhood cancer survivors who underwent radiotherapy in the pre-CT era, only 2D radiographs were acquired, th
Externí odkaz:
http://arxiv.org/abs/2002.07161
This report presents benchmarking results of the Hill-Valley Evolutionary Algorithm version 2019 (HillVallEA19) on the CEC2013 niching benchmark suite under the restrictions of the GECCO 2019 niching competition on multimodal optimization. Performanc
Externí odkaz:
http://arxiv.org/abs/1907.10988
Autor:
van Ooijen, I.M., Annink, K.V., Benders, M.J.N.L., Dudink, J., Alderliesten, T., Groenendaal, F., Tataranno, M.L., Lequin, M.H., Hoogduin, J.M., Visser, F., Raaijmakers, A.J.E., Klomp, D.W.J., Wiegers, E.C., Wijnen, J.P., van der Aa, N.E.
Publikováno v:
In Neuroimage: Reports June 2023 3(2)
