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1 Ergebnisse
1
Perioperative Predictions with Interpretable Latent Represe..:
, In:
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
,
Xue, Bing
;
Jiao, York
;
Kannampallil, Thomas
... - p. 4268-4278 , 2022
Link:
https://dl.acm.org/doi/10.1145/3534678.3539190
RT T1 <cTitle>Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining</cTitle>: T1 <Title>Perioperative Predictions with Interpretable Latent Representation</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3539190&Exemplar=1&LAN=DE A1 Xue, Bing A1 Jiao, York A1 Kannampallil, Thomas A1 Fritz, Bradley A1 King, Christopher A1 Abraham, Joanna A1 Avidan, Michael A1 Lu, Chenyang PB ACM YR 2022 K1 clinical application K1 deep latent variable models K1 healthcare prediction K1 latent interpretability K1 Mathematics of computing K1 Computing methodologies K1 Applied computing K1 Machine learning K1 Machine learning approaches K1 Learning in probabilistic graphical models K1 Latent variable models K1 Probability and statistics K1 Probabilistic reasoning algorithms K1 Variational methods SP 4268 OP 4278 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3534678.3539190 DO https://dl.acm.org/doi/10.1145/3534678.3539190 SF ELIB - SuUB Bremen
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