35 citations · 65 across the 3 of their papers we have counts for
3 papers
An automated machine learning framework to optimize radiomics model construction validated on twelve clinical applications
Martijn P. A. Starmans, Sebastian R. van der Voort, Thomas Phil +43
Predicting clinical outcomes from medical images using quantitative features (``radiomics'') requires many method design choices, Currently, in new clinical applications, finding t…
Differential diagnosis and molecular stratification of gastrointestinal stromal tumors on CT images using a radiomics approach
Martijn P. A. Starmans, Milea J. M. Timbergen, Melissa Vos +10
Distinguishing gastrointestinal stromal tumors (GISTs) from other intra-abdominal tumors and GISTs molecular analysis is necessary for treatment planning, but challenging due to it…
Extending Unsupervised Neural Image Compression With Supervised Multitask Learning
David Tellez, Diederik Hoppener, Cornelis Verhoef +5
We focus on the problem of training convolutional neural networks on gigapixel histopathology images to predict image-level targets. For this purpose, we extend Neural Image Compre…