A clustering‐based approach to address correlated features in predicting genitourinary toxicity from MRI‐guided prostate SBRT
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DOI: 10.1002/mp.17834
Abstract: It is common in outcome analysis to work with a large set of candidate prognostic features. However, such high‐dimensional input and relatively small sample size leads to risk of overfitting, low generalizability, and correlation bias. read more here.
Keywords: clustering based; approach address; correlated features; address correlated ... See more keywords