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  Conditional Generation of Medical Time Series for Extrapolation to Underrepresented Populations

Bing, S., Dittadi, A., Bauer, S., & Schwab, P. (2022). Conditional Generation of Medical Time Series for Extrapolation to Underrepresented Populations. PLOS Digital Health, 1(7): e0000074. doi:10.1371/journal.pdig.0000074.

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https://doi.org/10.1371/journal.pdig.0000074 (Publisher version)
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https://europepmc.org/article/MED/36812549 (Publisher version)
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 Creators:
Bing, Simon1, 2, Author                 
Dittadi, Andrea 2, Author
Bauer, Stefan2, Author
Schwab, Patrick 2, Author
Affiliations:
1Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society, Max-Planck-Ring 4, 72076 Tübingen, DE, ou_1497647              
2External Organizations, ou_persistent22              

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Free keywords: Abt. Schölkopf
 Abstract: -

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Language(s): eng - English
 Dates: 2022-07-19
 Publication Status: Published online
 Pages: 26
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1371/journal.pdig.0000074
arXiv: 2201.08186
BibTex Citekey: BinDitBauSch22
 Degree: -

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Title: PLOS Digital Health
Source Genre: Journal
 Creator(s):
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Publ. Info: San Francisco, CA : PLoS
Pages: - Volume / Issue: 1 (7) Sequence Number: e0000074 Start / End Page: - Identifier: ISSN: 2767-3170
CoNE: https://pure.mpg.de/cone/journals/resource/2767-3170