Accurate diagnosis and prognosis prediction of gastric cancer using deep learning on digital pathological images: A retrospective multicentre study

BACKGROUND: To reduce the high incidence and mortality of gastric cancer (GC), we aimed to develop deep learning-based models to assist in predicting the diagnosis and overall survival (OS) of GC patients using pathological images. METHODS: 2333 hematoxylin and eosin-stained pathological pictures of...

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Detalles Bibliográficos
Autores principales: Huang, Binglu, Tian, Shan, Zhan, Na, Ma, Jingjing, Huang, Zhiwei, Zhang, Chukang, Zhang, Hao, Ming, Fanhua, Liao, Fei, Ji, Mengyao, Zhang, Jixiang, Liu, Yinghui, He, Pengzhan, Deng, Beiying, Hu, Jiaming, Dong, Weiguo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Research paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8529077/
https://www.ncbi.nlm.nih.gov/pubmed/34678610
http://dx.doi.org/10.1016/j.ebiom.2021.103631

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8529077/
https://www.ncbi.nlm.nih.gov/pubmed/34678610
http://dx.doi.org/10.1016/j.ebiom.2021.103631

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