Tom Heskes, Ph.D.

Affiliations: 
Radboud University Nijmegen, Nijmegen, Gelderland, Netherlands 
Website:
http://www.cs.ru.nl/~tomh/
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Publications

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Lederer S, Heskes T, van Heeringen SJ, et al. (2020) Investigating the effect of dependence between conditions with Bayesian Linear Mixed Models for motif activity analysis. Plos One. 15: e0231824
Lederer S, Dijkstra TMH, Heskes T. (2019) Additive Dose Response Models: Defining Synergy. Frontiers in Pharmacology. 10: 1384
Lederer S, Dijkstra TMH, Heskes T. (2018) Additive Dose Response Models: Explicit Formulation and the Loewe Additivity Consistency Condition. Frontiers in Pharmacology. 9: 31
Thijssen B, Dijkstra TMH, Heskes T, et al. (2017) Bayesian data integration for quantifying the contribution of diverse measurements to parameter estimates. Bioinformatics (Oxford, England)
Ghafoorian M, Karssemeijer N, Heskes T, et al. (2017) Location Sensitive Deep Convolutional Neural Networks for Segmentation of White Matter Hyperintensities. Scientific Reports. 7: 5110
Ghafoorian M, Karssemeijer N, Heskes T, et al. (2017) Deep multi-scale location-aware 3D convolutional neural networks for automated detection of lacunes of presumed vascular origin. Neuroimage. Clinical. 14: 391-399
Ghafoorian M, Karssemeijer N, van Uden IW, et al. (2016) Automated detection of white matter hyperintensities of all sizes in cerebral small vessel disease. Medical Physics. 43: 6246
Thijssen B, Dijkstra TM, Heskes T, et al. (2016) BCM: toolkit for Bayesian analysis of Computational Models using samplers. Bmc Systems Biology. 10: 100
Cseke B, Zammit-Mangion A, Heskes T, et al. (2016) Sparse Approximate Inference for Spatio-Temporal Point Process Models Journal of the American Statistical Association. 111: 1746-1763
Hinne M, Janssen RJ, Heskes T, et al. (2015) Bayesian Estimation of Conditional Independence Graphs Improves Functional Connectivity Estimates. Plos Computational Biology. 11: e1004534
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