Deep-learning model accurately classifies multi-label lung ultrasound findings, enhancing diagnostic accuracy and inter-reader agreement

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Standort: Deutsche Nationalbibliothek Frankfurt am Main

Umfang: 1 Online-Ressource.

Sprache: Englisch

Erschienen in: Deep-learning model accurately classifies multi-label lung ultrasound findings, enhancing diagnostic accuracy and inter-reader agreement ; volume:14 ; number:1 ; day:27 ; month:9 ; year:2024 ; pages:1-9 ; date:12.2024
Scientific reports ; 14, Heft 1 (27.9.2024), 1-9, 12.2024

Urheber: Hong, Daeeon
Choi, Hyewon
Hong, Wonju
Kim, Yisak
Kim, Tae Jung
Choi, Jinwook
Ko, Sang-Bae
Park, Chang Min

Beteiligte Personen und Organisationen: SpringerLink (Online service)

DOI: 10.1038/s41598-024-72484-y

URN: urn:nbn:de:101:1-2412132127446.691127253972

Rechteinformation: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Letzte Aktualisierung: 15.08.2025, 07:36 MESZ

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Beteiligte

Hong, Daeeon
Choi, Hyewon
Hong, Wonju
Kim, Yisak
Kim, Tae Jung
Choi, Jinwook
Ko, Sang-Bae
Park, Chang Min
SpringerLink (Online service)

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Deep-learning model accurately classifies multi-label lung ultrasound findings, enhancing diagnostic accuracy and inter-reader agreement

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