332 citations · 378 across the 6 of their papers we have counts for
6 papers
Sparse canonical correlation analysis for multiple measurements with latent trajectories
Nuria Senar, Aeilko H. Zwinderman, Michel H. Hof and
Canonical Correlation Analysis, CCA, is a widely used multivariate method in omics research for integrating high dimensional datasets. CCA identifies hidden links by deriving linea…
Segmentation of glioblastomas in early post-operative multi-modal MRI with deep neural networks
Ragnhild Holden Helland, Alexandros Ferles, André Pedersen +30
Extent of resection after surgery is one of the main prognostic factors for patients diagnosed with glioblastoma. To achieve this, accurate segmentation and classification of resid…
Preoperative brain tumor imaging: models and software for segmentation and standardized reporting
D. Bouget, A. Pedersen, A. S. Jakola +27
For patients suffering from brain tumor, prognosis estimation and treatment decisions are made by a multidisciplinary team based on a set of preoperative MR scans. Currently, the l…
Covered Information Disentanglement: Model Transparency via Unbiased Permutation Importance
João Pereira, Erik S. G. Stroes, Aeilko H. Zwinderman +1
Model transparency is a prerequisite in many domains and an increasingly popular area in machine learning research. In the medical domain, for instance, unveiling the mechanisms be…
Interpretable Models via Pairwise permutations algorithm
Troy Maaslandand, João Pereira, Diogo Bastos +4
One of the most common pitfalls often found in high dimensional biological data sets are correlations between the features. This may lead to statistical and machine learning method…
On the Benjamini--Hochberg method
J. A. Ferreira, A. H. Zwinderman
We investigate the properties of the Benjamini--Hochberg method for multiple testing and of a variant of Storey's generalization of it, extending and complementing the asymptotic a…