Reproducible radiomics through automated machine learning validated on twelve clinical applications. (arXiv:2108.08618v2 [eess.IV] UPDATED)

Radiomics uses quantitative medical imaging features to predict clinical
outcomes. Currently, in a new clinical application, finding the optimal
radiomics method out of the wide range of available options has to be done
manually through a heuristic trial-and-error process. In this study we propose
a framework for automatically optimizing the construction of radiomics
workflows per application. To this end, we formulate radiomics as a modular
workflow and include a large collection of common algorithms for each
component. To optimize the …

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