Detection of diabetes from whole-body MRI using deep learning

Dietz, Benedikt; Machann, Jürgen; Agrawal, Vaibhav; Heni, Martin; Schwab, Patrick; Dienes, Julia; Reichert, Steffen; Birkenfeld, Andreas L.; Häring, Hans-Ulrich; Schick, Fritz; Stefan, Norbert; Fritsche, Andreas; Preissl, Hubert; Schölkopf, Bernhard; Bauer, Stefan; Wagner, Robert

doi:10.1172/jci.insight.146999

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Detection of diabetes from whole-body MRI using deep learning

Dietz, B., Machann, J., Agrawal, V., Heni, M., Schwab, P., Dienes, J., et al. (2021). Detection of diabetes from whole-body MRI using deep learning. JCI Insight, 6(21): e146999. doi:10.1172/jci.insight.146999.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0010-30E7-3 Version Permalink: https://hdl.handle.net/21.11116/0000-0010-30E8-2

Genre: Journal Article

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https://doi.org/10.1172/jci.insight.146999 (Publisher version) Open Access Gold

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https://europepmc.org/article/MED/34591793 (Publisher version) Open Access Green

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Creators:
Dietz, Benedikt ¹, Author
Machann, Jürgen ¹, Author
Agrawal, Vaibhav², Author
Heni, Martin ¹, Author
Schwab, Patrick ¹, Author
Dienes, Julia ¹, Author
Reichert, Steffen ¹, Author
Birkenfeld, Andreas L.¹, Author
Häring, Hans-Ulrich¹, Author
Schick, Fritz ¹, Author
Stefan, Norbert ¹, Author
Fritsche, Andreas ¹, Author
Preissl, Hubert ¹, Author
Schölkopf, Bernhard², Author
Bauer, Stefan², Author
Wagner, Robert ¹, Author

Affiliations:
1External Organizations, ou_persistent22
2Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society, ou_1497647

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Free keywords: Abt. Schölkopf

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Language(s): eng - English

Dates: Published Online: 2021-09-30Date issued: 2021-11-08

Publication Status: Issued

Pages: 12

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Table of Contents: -

Rev. Type: Peer

Identifiers: DOI: 10.1172/jci.insight.146999
URI: https://europepmc.org/article/MED/34591793
BibTex Citekey: Dietzetal21

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Title: JCI Insight

Source Genre: Journal

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Publ. Info: Ann Arbor : American Society for Clinical Investigation (ASCI)

Pages: - Volume / Issue: 6 (21) Sequence Number: e146999 Start / End Page: - Identifier: ISSN: 2379-3708
CoNE: https://pure.mpg.de/cone/journals/resource/2379-3708