Quantifying central canal stenosis prediction uncertainty in SpineNet with conformal prediction

Abstract This study applies conformal prediction (CP) to SpineNet to quantify prediction uncertainty in the classification of central canal stenosis (CCS) into four grades: normal, mild, moderate, and severe. CP provides prediction sets rather than singleton predictions with a guaranteed probability...

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Bibliografiske detaljer

Principais autores:	Andrea Cina, Maria Monzon, Fabio Galbusera, Catherine R. Jutzeler
Format:	Artigo
Sprog:	Inglês
Udgivet:	Nature Portfolio 2026-01-01
Serier:	Scientific Reports
Fag:	Conformal prediction Uncertainty Stenosis SpineNet Deep learning
Online adgang:	https://doi.org/10.1038/s41598-026-35343-6
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