Measuring the bias of incorrect application of feature selection when using cross-validation in radiomics
Abstract Background Many studies in radiomics are using feature selection methods to identify the most predictive features. At the same time, they employ cross-validation to estimate the performance of the developed models. However, if the feature selection is performed before the cross-validation,...
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| Format: | Article |
| Language: | English |
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SpringerOpen
2021-11-01
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| Series: | Insights into Imaging |
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| Online Access: | https://doi.org/10.1186/s13244-021-01115-1 |