Use of Endoscopic Images in the Prediction of Submucosal Invasion of Gastric Neoplasms: Automated Deep Learning Model Development and Usability Study

BACKGROUND: In a previous study, we examined the use of deep learning models to classify the invasion depth (mucosa-confined versus submucosa-invaded) of gastric neoplasms using endoscopic images. The external test accuracy reached 77.3%. However, model establishment is labor intense, requiring high...

Descripción completa

Detalles Bibliográficos
Autores principales: Bang, Chang Seok, Lim, Hyun, Jeong, Hae Min, Hwang, Sung Hyeon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2021
Materias:
Original Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8085753/
https://www.ncbi.nlm.nih.gov/pubmed/33856356
http://dx.doi.org/10.2196/25167

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8085753/
https://www.ncbi.nlm.nih.gov/pubmed/33856356
http://dx.doi.org/10.2196/25167

Ejemplares similares