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eess.IV2021★ 11 cited
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…
eess.IV2021
Evaluating glioma growth predictions as a forward ranking problem
Karin A. van Garderen, Sebastian R. van der Voort, Maarten M. J. Wijnenga +6
The problem of tumor growth prediction is challenging, but promising results have been achieved with both model-driven and statistical methods. In this work, we present a framework…