A Novel Model Based on Deep Convolutional Neural Network Improves Diagnostic Accuracy of Intramucosal Gastric Cancer (With Video)

BACKGROUND AND AIMS: Prediction of intramucosal gastric cancer (GC) is a big challenge. It is not clear whether artificial intelligence could assist endoscopists in the diagnosis. METHODS: A deep convolutional neural networks (DCNN) model was developed via retrospectively collected 3407 endoscopic i...

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Detalles Bibliográficos
Autores principales: Tang, Dehua, Zhou, Jie, Wang, Lei, Ni, Muhan, Chen, Min, Hassan, Shahzeb, Luo, Renquan, Chen, Xi, He, Xinqi, Zhang, Lihui, Ding, Xiwei, Yu, Honggang, Xu, Guifang, Zou, Xiaoping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Oncology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8095170/
https://www.ncbi.nlm.nih.gov/pubmed/33959495
http://dx.doi.org/10.3389/fonc.2021.622827

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8095170/
https://www.ncbi.nlm.nih.gov/pubmed/33959495
http://dx.doi.org/10.3389/fonc.2021.622827

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