Artificial intelligence for ovarian cancer diagnosis via ultrasound: a systematic review and quantitative assessment of model performance.

Front Artif Intell · 2025 · PMC12627067 · PMID 41267815

Europe PMC DOI

hedged sentences

0.0960

closest p · 1.9× alpha

0.0960

boldest claim

The sentences

approached significancep = 0.096so close (0.05 < p ≤ 0.1)

However, the effect of high risk of bias approached significance ( β = 0.0427, p = 0.096), suggesting a possible inflation of performance estimates in studies with methodological limitations.

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did not reach statistical significanceno p-value reported

The regression included 26 studies with complete data and demonstrated that segmentation type was a significant predictor of accuracy ( β = 0.0656, p = 0.007), while the other covariates did not reach statistical significance.

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