Policy Learning for Actively Labeled Sample Selection on Lumbar Semi-supervised Classification.

Large labeled data bring significant performance improvement, but acquiring labeled medical data is particularly challenging due to the laborious, time-consuming, and medically qualified annotation. Semi-supervised learning has been employed to leverage unlabeled data. However, the quality and quant...

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Bibliographic Details

Published in:	Journal of Imaging Informatics in Medicine Vol. 38; no. 1; pp. 165 - 177
Main Authors:	Hai, Jinjin, Chen, Jian, Qiao, Kai, Su, Zhihai, Lu, Hai, Yan, Bin
Format:	diagnostic images equations & formulas research tables/charts Journal Article
Published:	Springer Nature Feb2025
Online Access:	View this record in EBSCOhost