Machine learning predicts lymph node metastasis of poorly differentiated-type intramucosal gastric cancer
Abstract To construct a machine learning algorithm model of lymph node metastasis (LNM) in patients with poorly differentiated-type intramucosal gastric cancer. 1169 patients with postoperative gastric cancer were divided into a training group and a test group at a ratio of 7:3. The model for lymph...
Guardado en:
Autores principales: | Cheng-Mao Zhou, Ying Wang, Hao-Tian Ye, Shuping Yan, Muhuo Ji, Panmiao Liu, Jian-Jun Yang |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/b60c9cebea0d48e682d873e771fbfc51 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
A nomogram to predict risk of lymph node metastasis in early gastric cancer
por: Miaoquan Zhang, et al.
Publicado: (2021) -
A case of early gastric cancer with a single giant lymph node metastasis
por: Masato Yoshikawa, et al.
Publicado: (2021) -
Upregulation of lncRNA BANCR associated with the lymph node metastasis and poor prognosis in colorectal cancer
por: Shen,Xiaogang, et al.
Publicado: (2017) -
Positive lymph node ratio is an index in predicting prognosis for remnant gastric cancer with insufficient retrieved lymph node in R0 resection
por: Honghu Wang, et al.
Publicado: (2021) -
Retropharyngeal lymph node metastasis on N stage of nasopharyngeal carcinoma.
por: Xin-Bin Pan, et al.
Publicado: (2021)