Hybrid AI-assistive diagnostic model permits rapid TBS classification of cervical liquid-based thin-layer cell smears

Technical advancements significantly improve earlier diagnosis of cervical cancer, but accurate diagnosis is still difficult due to various factors. We develop an artificial intelligence assistive diagnostic solution, AIATBS, to improve cervical liquid-based thin-layer cell smear diagnosis according...

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Detalles Bibliográficos
Autores principales: Zhu, Xiaohui, Li, Xiaoming, Ong, Kokhaur, Zhang, Wenli, Li, Wencai, Li, Longjie, Young, David, Su, Yongjian, Shang, Bin, Peng, Linggan, Xiong, Wei, Liu, Yunke, Liao, Wenting, Xu, Jingjing, Wang, Feifei, Liao, Qing, Li, Shengnan, Liao, Minmin, Li, Yu, Rao, Linshang, Lin, Jinquan, Shi, Jianyuan, You, Zejun, Zhong, Wenlong, Liang, Xinrong, Han, Hao, Zhang, Yan, Tang, Na, Hu, Aixia, Gao, Hongyi, Cheng, Zhiqiang, Liang, Li, Yu, Weimiao, Ding, Yanqing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8192526/
https://www.ncbi.nlm.nih.gov/pubmed/34112790
http://dx.doi.org/10.1038/s41467-021-23913-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8192526/
https://www.ncbi.nlm.nih.gov/pubmed/34112790
http://dx.doi.org/10.1038/s41467-021-23913-3

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