Conditional autoencoder pre-training and optimization algorithms for personalized care of hemophiliac patients

This paper presents the use of deep conditional autoencoder to predict the effect of treatments for patients suffering from hemophiliac disorders. Conditional autoencoder is a semi-supervised model that learns an abstract representation of the data and provides conditional reconstruction capabilitie...

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Bibliographic Details

Published in:	Frontiers in artificial intelligence Vol. 6; p. 1048010
Main Authors:	Buche, Cédric, Lasson, François, Kerdelo, Sébastien
Format:	Journal Article
Language:	English
Published:	Switzerland Frontiers Media S.A 25.01.2023
Subjects:	Artificial Intelligence autoencoder Computer Science conditional pre-training deep learning global assays hemophilia incremental optimization deep learning hemophilia conditional pre-training autoencoder global assays incremental optimization
ISSN:	2624-8212, 2624-8212
Online Access:	Get full text
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