Using Genomics Feature Selection Method in Radiomics Pipeline Improves Prognostication Performance in Locally Advanced Esophageal Squamous Cell Carcinoma-A Pilot Study.

Cancers (Basel) · 2021 · PMC8124289 · PMID 33946826

Europe PMC DOI

hedged sentence

0.0530

closest p · 1.1× alpha

0.0530

boldest claim

The sentences

borderline significantp = 0.053so close (0.05 < p ≤ 0.1)

[ 43 ] developed a CT-based radiomic model with an AUC of 0.61 and borderline significant Kaplan–Meier curve result in the validation dataset ( p = 0.053).

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