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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...
Autores principales: | Bang, Chang Seok, Lim, Hyun, Jeong, Hae Min, Hwang, Sung Hyeon |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2021
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Materias: | |
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 |
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