Multi-center verification of the influence of data ratio of training sets on test results of an AI system for detecting early gastric cancer based on the YOLO-v4 algorithm

OBJECTIVE: Convolutional Neural Network(CNN) is increasingly being applied in the diagnosis of gastric cancer. However, the impact of proportion of internal data in the training set on test results has not been sufficiently studied. Here, we constructed an artificial intelligence (AI) system called...

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Detalles Bibliográficos
Autores principales: Jin, Tao, Jiang, Yancai, Mao, Boneng, Wang, Xing, Lu, Bo, Qian, Ji, Zhou, Hutao, Ma, Tieliang, Zhang, Yefei, Li, Sisi, Shi, Yun, Yao, Zhendong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Oncology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9425091/
https://www.ncbi.nlm.nih.gov/pubmed/36052264
http://dx.doi.org/10.3389/fonc.2022.953090

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9425091/
https://www.ncbi.nlm.nih.gov/pubmed/36052264
http://dx.doi.org/10.3389/fonc.2022.953090

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