11 citations · 21 across the 2 of their papers we have counts for
2 papers
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…
cs.CV2019★ 10 cited
Towards Unsupervised Cancer Subtyping: Predicting Prognosis Using A Histologic Visual Dictionary
Hassan Muhammad, Carlie S. Sigel, Gabriele Campanella +9
Unlike common cancers, such as those of the prostate and breast, tumor grading in rare cancers is difficult and largely undefined because of small sample sizes, the sheer volume of…