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Assisting Clinical Decisions for Scarcely Available Treatme..:

, In: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining,

Xue, Bing ; Said, Ahmed Sameh ; Xu, Ziqi... - p. 5360-5371 , 2023

Link: https://dl.acm.org/doi/10.1145/3580305.3599774

RT 
T1 <cTitle>Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining</cTitle>: T1 <Title>Assisting Clinical Decisions for Scarcely Available Treatment via Disentangled Latent Representation</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-3599774&Exemplar=1&LAN=DE
				
A1 Xue, Bing
A1 Said, Ahmed Sameh
A1 Xu, Ziqi
A1 Liu, Hanyang
A1 Shah, Neel
A1 Yang, Hanqing
A1 Payne, Philip
A1 Lu, Chenyang
PB ACM
YR 2023
K1 causal inference
K1 covid analysis
K1 deep latent variable models
K1 generative ai
K1 machine learning for healthcare
K1 representation learning
K1 semi-supervised learning
K1 treatment effect estimation
K1 variational autoencoder
K1 Computing methodologies
K1 Machine learning
K1 Learning paradigms
K1 Unsupervised learning
K1 Dimensionality reduction and manifold learning
K1 Learning settings
K1 Semi-supervised learning settings
K1 Applied computing
K1 Life and medical sciences
K1 Bioinformatics
K1 Machine learning approaches
K1 Learning latent representations
K1 Health informatics
K1 Neural networks
SP 5360
OP 5371
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3580305.3599774
DO https://dl.acm.org/doi/10.1145/3580305.3599774
SF ELIB - SuUB Bremen

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