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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Bibliografske podrobnosti

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