Medical Data Wrangling With Sequential Variational Autoencoders

Medical data sets are usually corrupted by noise and missing data. These missing patterns are commonly assumed to be completely random, but in medical scenarios, the reality is that these patterns occur in bursts due to sensors that are off for some time or data collected in a misaligned uneven fash...

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Veröffentlicht in:	IEEE journal of biomedical and health informatics Jg. 26; H. 6; S. 2737 - 2745
Hauptverfasser:	Barrejon, Daniel, Olmos, Pablo M., Artes-Rodriguez, Antonio
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.06.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Computer applications Correlation Cross correlation Data models Databases, Factual Deep learning heterogeneous Hospitals Humans Measurement Medical records Missing data Monitoring Root-mean-square errors sequential data Standard error Time series analysis VAE
ISSN:	2168-2194, 2168-2208, 2168-2208
Online-Zugang:	Volltext
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