Predicting Survival Outcomes in the Presence of Unlabeled Data

dc.contributor.author	Nateghi, Fateme
dc.contributor.author	Vens, Celine
dc.contributor.imecauthor	Nateghi, Fateme
dc.contributor.imecauthor	Vens, Celine
dc.contributor.orcidimec	Nateghi, Fateme::0000-0002-8874-8835
dc.contributor.orcidimec	Vens, Celine::0000-0003-0983-256X
dc.date.accessioned	2023-05-16T09:51:00Z
dc.date.available	2022-11-04T02:53:01Z
dc.date.available	2023-03-31T08:38:43Z
dc.date.available	2023-05-16T09:51:00Z
dc.date.issued	2022-10-26
dc.description.wosFundingText	This work was supported by KU Leuven Internal Funds (grant 3M180314). The authors also acknowledge the Flemish Government (AI Research Program).
dc.identifier.doi	10.1007/s10994-022-06257-x
dc.identifier.issn	0885-6125
dc.identifier.uri	https://imec-publications.be/handle/20.500.12860/40670
dc.publisher	SPRINGER
dc.source.beginpage	4139
dc.source.endpage	4157
dc.source.issue	11
dc.source.journal	MACHINE LEARNING
dc.source.numberofpages	19
dc.source.volume	111
dc.subject.discipline	Computer science/information technology
dc.subject.keywords	REGRESSION
dc.subject.keywords	MODEL
dc.title	Predicting Survival Outcomes in the Presence of Unlabeled Data
dc.type	Journal article
dspace.entity.type	Publication
Files
Publication available in collections:	Articles