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1 Ergebnisse
1
MoCLIM: Towards Accurate Cancer Subtyping via Multi-Omics C..:
, In:
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management
,
Yang, Ziwei
;
Chen, Zheng
;
Matsubara, Yasuko
. - p. 2895-2905 , 2023
Link:
https://dl.acm.org/doi/10.1145/3583780.3614970
RT T1 <cTitle>Proceedings of the 32nd ACM International Conference on Information and Knowledge Management</cTitle>: T1 <Title>MoCLIM: Towards Accurate Cancer Subtyping via Multi-Omics Contrastive Learning with Omics-Inference Modeling</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3614970&Exemplar=1&LAN=DE A1 Yang, Ziwei A1 Chen, Zheng A1 Matsubara, Yasuko A1 Sakurai, Yasushi PB ACM YR 2023 K1 cancer subtypes K1 contrastive learning K1 multi-omics data K1 Computing methodologies K1 Machine learning K1 Machine learning approaches K1 Neural networks K1 Applied computing K1 Life and medical sciences K1 Bioinformatics SP 2895 OP 2905 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3583780.3614970 DO https://dl.acm.org/doi/10.1145/3583780.3614970 SF ELIB - SuUB Bremen
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