Dermal features derived from optoacoustic tomograms via machine learning correlate microangiopathy phenotypes with diabetes stage
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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1 Online-Ressource.
- Sprache
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Englisch
- Erschienen in
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Dermal features derived from optoacoustic tomograms via machine learning correlate microangiopathy phenotypes with diabetes stage ; volume:7 ; number:12 ; day:4 ; month:12 ; year:2023 ; pages:1667-1682 ; date:12.2023
Nature biomedical engineering ; 7, Heft 12 (4.12.2023), 1667-1682, 12.2023
- Urheber
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Karlas, Angelos
Katsouli, Nikoletta
Fasoula, Nikolina-Alexia
Bariotakis, Michail
Chlis, Nikolaos-Kosmas
Omar, Murad
He, Hailong
Iakovakis, Dimitrios
Schäffer, Christoph
Kallmayer, Michael
Füchtenbusch, Martin
Ziegler, Annette
Eckstein, Hans-Henning
Hadjileontiadis, Leontios
Ntziachristos, Vasilis
- Beteiligte Personen und Organisationen
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SpringerLink (Online service)
- DOI
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10.1038/s41551-023-01151-w
- URN
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urn:nbn:de:101:1-2024030221060299048300
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
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14.08.2025, 10:45 MESZ
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Beteiligte
- Karlas, Angelos
- Katsouli, Nikoletta
- Fasoula, Nikolina-Alexia
- Bariotakis, Michail
- Chlis, Nikolaos-Kosmas
- Omar, Murad
- He, Hailong
- Iakovakis, Dimitrios
- Schäffer, Christoph
- Kallmayer, Michael
- Füchtenbusch, Martin
- Ziegler, Annette
- Eckstein, Hans-Henning
- Hadjileontiadis, Leontios
- Ntziachristos, Vasilis
- SpringerLink (Online service)
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