radMLBench: A dataset collection for benchmarking in radiomics.
Journal:
Computers in biology and medicine
Published Date:
Sep 12, 2024
Abstract
BACKGROUND: New machine learning methods and techniques are frequently introduced in radiomics, but they are often tested on a single dataset, which makes it challenging to assess their true benefit. Currently, there is a lack of a larger, publicly accessible dataset collection on which such assessments could be performed. In this study, a collection of radiomics datasets with binary outcomes in tabular form was curated to allow benchmarking of machine learning methods and techniques.