Development and validation of a machine learning-based radiomics model using 45-keV virtual monoenergetic images for differentiating fat-poor angiomyolipoma from clear cell renal cell carcinoma.

Transl Androl Urol · 2026 · PMC13263835 · PMID 42293856

Europe PMC DOI

hedged sentence

0.0600

closest p · 1.2× alpha

0.0600

boldest claim

The sentences

showed a trendP=0.06so close (0.05 < p ≤ 0.1)

did not reach statistical significanceno p-value reported

However, in the validation set, the dual-phase model showed a trend toward higher AUC than the NP model for LR (ΔAUC =0.211, P=0.06) and SVM (ΔAUC =0.159, P=0.10), although these differences did not reach statistical significance.

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