An Optimal Artificial Intelligence System for Real-Time Endoscopic Prediction of Invasion Depth in Early Gastric Cancer

SIMPLE SUMMARY: We previously constructed a VGG-16-based artificial intelligence (AI) model (image classifier [IC]) to predict the invasion depth in early gastric cancer (EGC) using static images. However, images cannot capture the spatio-temporal information available during real-time endoscopy. Th...

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Detalles Bibliográficos
Autores principales: Kim, Jie-Hyun, Oh, Sang-Il, Han, So-Young, Keum, Ji-Soo, Kim, Kyung-Nam, Chun, Jae-Young, Youn, Young-Hoon, Park, Hyojin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9741000/
https://www.ncbi.nlm.nih.gov/pubmed/36497481
http://dx.doi.org/10.3390/cancers14236000

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9741000/
https://www.ncbi.nlm.nih.gov/pubmed/36497481
http://dx.doi.org/10.3390/cancers14236000

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