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

Technical advancements have significantly improved early diagnosis of cervical cancer, but accurate diagnosis is still difficult due to various practical factors. Here, the authors develop an artificial intelligence assistive diagnostic solution to improve cervical liquid-based thin-layer cell smear...

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Autores principales: Xiaohui Zhu, Xiaoming Li, Kokhaur Ong, Wenli Zhang, Wencai Li, Longjie Li, David Young, Yongjian Su, Bin Shang, Linggan Peng, Wei Xiong, Yunke Liu, Wenting Liao, Jingjing Xu, Feifei Wang, Qing Liao, Shengnan Li, Minmin Liao, Yu Li, Linshang Rao, Jinquan Lin, Jianyuan Shi, Zejun You, Wenlong Zhong, Xinrong Liang, Hao Han, Yan Zhang, Na Tang, Aixia Hu, Hongyi Gao, Zhiqiang Cheng, Li Liang, Weimiao Yu, Yanqing Ding
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Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/a9ff146cba1f4537910e4022e670fbb3
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spelling oai:doaj.org-article:a9ff146cba1f4537910e4022e670fbb32021-12-02T17:52:29ZHybrid AI-assistive diagnostic model permits rapid TBS classification of cervical liquid-based thin-layer cell smears10.1038/s41467-021-23913-32041-1723https://doaj.org/article/a9ff146cba1f4537910e4022e670fbb32021-06-01T00:00:00Zhttps://doi.org/10.1038/s41467-021-23913-3https://doaj.org/toc/2041-1723Technical advancements have significantly improved early diagnosis of cervical cancer, but accurate diagnosis is still difficult due to various practical factors. Here, the authors develop an artificial intelligence assistive diagnostic solution to improve cervical liquid-based thin-layer cell smear diagnosis according to clinical TBS criteria in a large multicenter study.Xiaohui ZhuXiaoming LiKokhaur OngWenli ZhangWencai LiLongjie LiDavid YoungYongjian SuBin ShangLinggan PengWei XiongYunke LiuWenting LiaoJingjing XuFeifei WangQing LiaoShengnan LiMinmin LiaoYu LiLinshang RaoJinquan LinJianyuan ShiZejun YouWenlong ZhongXinrong LiangHao HanYan ZhangNa TangAixia HuHongyi GaoZhiqiang ChengLi LiangWeimiao YuYanqing DingNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-12 (2021)
institution DOAJ
collection DOAJ
language EN
topic Science
Q
spellingShingle Science
Q
Xiaohui Zhu
Xiaoming Li
Kokhaur Ong
Wenli Zhang
Wencai Li
Longjie Li
David Young
Yongjian Su
Bin Shang
Linggan Peng
Wei Xiong
Yunke Liu
Wenting Liao
Jingjing Xu
Feifei Wang
Qing Liao
Shengnan Li
Minmin Liao
Yu Li
Linshang Rao
Jinquan Lin
Jianyuan Shi
Zejun You
Wenlong Zhong
Xinrong Liang
Hao Han
Yan Zhang
Na Tang
Aixia Hu
Hongyi Gao
Zhiqiang Cheng
Li Liang
Weimiao Yu
Yanqing Ding
Hybrid AI-assistive diagnostic model permits rapid TBS classification of cervical liquid-based thin-layer cell smears
description Technical advancements have significantly improved early diagnosis of cervical cancer, but accurate diagnosis is still difficult due to various practical factors. Here, the authors develop an artificial intelligence assistive diagnostic solution to improve cervical liquid-based thin-layer cell smear diagnosis according to clinical TBS criteria in a large multicenter study.
format article
author Xiaohui Zhu
Xiaoming Li
Kokhaur Ong
Wenli Zhang
Wencai Li
Longjie Li
David Young
Yongjian Su
Bin Shang
Linggan Peng
Wei Xiong
Yunke Liu
Wenting Liao
Jingjing Xu
Feifei Wang
Qing Liao
Shengnan Li
Minmin Liao
Yu Li
Linshang Rao
Jinquan Lin
Jianyuan Shi
Zejun You
Wenlong Zhong
Xinrong Liang
Hao Han
Yan Zhang
Na Tang
Aixia Hu
Hongyi Gao
Zhiqiang Cheng
Li Liang
Weimiao Yu
Yanqing Ding
author_facet Xiaohui Zhu
Xiaoming Li
Kokhaur Ong
Wenli Zhang
Wencai Li
Longjie Li
David Young
Yongjian Su
Bin Shang
Linggan Peng
Wei Xiong
Yunke Liu
Wenting Liao
Jingjing Xu
Feifei Wang
Qing Liao
Shengnan Li
Minmin Liao
Yu Li
Linshang Rao
Jinquan Lin
Jianyuan Shi
Zejun You
Wenlong Zhong
Xinrong Liang
Hao Han
Yan Zhang
Na Tang
Aixia Hu
Hongyi Gao
Zhiqiang Cheng
Li Liang
Weimiao Yu
Yanqing Ding
author_sort Xiaohui Zhu
title Hybrid AI-assistive diagnostic model permits rapid TBS classification of cervical liquid-based thin-layer cell smears
title_short Hybrid AI-assistive diagnostic model permits rapid TBS classification of cervical liquid-based thin-layer cell smears
title_full Hybrid AI-assistive diagnostic model permits rapid TBS classification of cervical liquid-based thin-layer cell smears
title_fullStr Hybrid AI-assistive diagnostic model permits rapid TBS classification of cervical liquid-based thin-layer cell smears
title_full_unstemmed Hybrid AI-assistive diagnostic model permits rapid TBS classification of cervical liquid-based thin-layer cell smears
title_sort hybrid ai-assistive diagnostic model permits rapid tbs classification of cervical liquid-based thin-layer cell smears
publisher Nature Portfolio
publishDate 2021
url https://doaj.org/article/a9ff146cba1f4537910e4022e670fbb3
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