Development and validation of a feature extraction-based logical anthropomorphic diagnostic system for early gastric cancer: A case-control study

BACKGROUND: Prompt diagnosis of early gastric cancer (EGC) is crucial for improving patient survival. However, most previous computer-aided-diagnosis (CAD) systems did not concretize or explain diagnostic theories. We aimed to develop a logical anthropomorphic artificial intelligence (AI) diagnostic...

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Detalles Bibliográficos
Autores principales: Li, Jia, Zhu, Yijie, Dong, Zehua, He, Xinqi, Xu, Ming, Liu, Jun, Zhang, Mengjiao, Tao, Xiao, Du, Hongliu, Chen, Di, Huang, Li, Shang, Renduo, Zhang, Lihui, Luo, Renquan, Zhou, Wei, Deng, Yunchao, Huang, Xu, Li, Yanxia, Chen, Boru, Gong, Rongrong, Zhang, Chenxia, Li, Xun, Wu, Lianlian, Yu, Honggang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9061989/
https://www.ncbi.nlm.nih.gov/pubmed/35521066
http://dx.doi.org/10.1016/j.eclinm.2022.101366

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9061989/
https://www.ncbi.nlm.nih.gov/pubmed/35521066
http://dx.doi.org/10.1016/j.eclinm.2022.101366

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