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An artificial intelligence system for comprehensive pathologic outcome prediction in early gastric cancer through endoscopic image analysis (with video)

Crossref DOI link: https://doi.org/10.1007/s10120-024-01524-3

Published Online: 2024-07-02

Published Print: 2024-09

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Lee, Seunghan

Jeon, Jiwoon

Park, Jinbae

Chang, Young Hoon

Shin, Cheol Min

Oh, Mi Jin

Kim, Su Hyun

Kang, Seungkyung

Park, Su Hee

Kim, Sang Gyun

Lee, Hyuk-Joon

Yang, Han-Kwang

Lee, Hey Seung

Cho, Soo-Jeong https://orcid.org/0000-0001-7144-0589
Funding

Funding for this research was provided by:

National Research Foundation of Korea (#NRF-2022R1A2B5B01001430)

Korean Society of Gastrointestinal Endoscopy

Ainex Corporation

Seoul National University
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Text and Data Mining valid from 2024-07-02

Version of Record valid from 2024-07-02
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Article History

Received: 15 February 2024

Accepted: 18 June 2024

First Online: 2 July 2024

Change Date: 4 September 2024

Change Type: Correction

Change Details: A Correction to this paper has been published:

Change Details: https://doi.org/10.1007/s10120-024-01549-8

Updates are available Correction dated 2024-09-04

Click to view Correction: https://doi.org/10.1007/s10120-024-01549-8