Correction: Deep learning model for differentiating nasal cavity masses based on nasal endoscopy images
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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1 Online-Ressource.
- Language
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Englisch
- Bibliographic citation
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Correction: Deep learning model for differentiating nasal cavity masses based on nasal endoscopy images ; volume:24 ; number:1 ; day:3 ; month:6 ; year:2024 ; pages:1 ; date:12.2024
BMC medical informatics and decision making ; 24, Heft 1 (3.6.2024), 1, 12.2024
- Creator
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Tai, Junhu
Han, Munsoo
Choi, Bo Yoon
Kang, Sung Hoon
Kim, Hyeongeun
Kwak, Jiwon
Lee, Dabin
Lee, Tae Hoon
Cho, Yongwon
Kim, Tae Hoon
- Contributor
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SpringerLink (Online service)
- DOI
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10.1186/s12911-024-02562-8
- URN
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urn:nbn:de:101:1-2408102127170.060199553498
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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14.08.2025, 10:51 AM CEST
Data provider
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Associated
- Tai, Junhu
- Han, Munsoo
- Choi, Bo Yoon
- Kang, Sung Hoon
- Kim, Hyeongeun
- Kwak, Jiwon
- Lee, Dabin
- Lee, Tae Hoon
- Cho, Yongwon
- Kim, Tae Hoon
- SpringerLink (Online service)
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Deep learning model for differentiating nasal cavity masses based on nasal endoscopy images
The Nasal Cavity.
Epithelioid Hemangioendothelioma of Nasal Cavity
Angioleiomyoma of the Nasal Cavity
NasalSeg: A Dataset for Automatic Segmentation of Nasal Cavity and Paranasal Sinuses from 3D CT Images
Numerical analysis of nasal cavity flows
Malignant ectomesenchymoma of the nasal cavity
The nasal cavity microbiota of healthy adults
Nasal cavity perforation by implant fixtures: case series with emphasis on panoramic imaging of nasal cavity extending posteriorly
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