Artificial intelligence annotated clinical-pathologic risk model to predict outcomes of advanced gastric cancer

BACKGROUND: Gastric cancer with synchronous distant metastases indicates a dismal prognosis. The success in survival improvement mainly relies on our ability to predict the potential benefit of a therapy. Our objective is to develop an artificial intelligence annotated clinical-pathologic risk model...

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Detalles Bibliográficos
Autores principales: Chen, Yan, Shou, Lin, Xia, Ying, Deng, Yanju, Li, Qianguo, Huang, Zhishuang, Li, Youlan, Li, Yanmei, Cai, Wenliang, Wang, Yueshan, Cheng, Yingying, Chen, Hongzhuan, Wan, Li
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Oncology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10086433/
https://www.ncbi.nlm.nih.gov/pubmed/37056330
http://dx.doi.org/10.3389/fonc.2023.1099360

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10086433/
https://www.ncbi.nlm.nih.gov/pubmed/37056330
http://dx.doi.org/10.3389/fonc.2023.1099360

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