EP142/#1526  Study on the effectiveness of using artificial intelligence image recognition system to diagnose endometrial cytopathology

Jing An; Panyue Yin; Bin Wang; Guizhi Shi; Dexing Zhong; Jianliu Wang; Qiling Li

doi:10.1136/ijgc-2023-IGCS.237

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AS04. Endometrial/Uterine corpus cancers

EP142/#1526 Study on the effectiveness of using artificial intelligence image recognition system to diagnose endometrial cytopathology

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Jing An The First Affiliated Hospital of Xi’an Jiaotong University, Department of Obstetrics and Gynecology, Xi’an, China PubMed articles Google scholar articles
Panyue Yin The First Affiliated Hospital of Xi’an Jiaotong University, Department of Obstetrics and Gynecology, Xi’an, China PubMed articles Google scholar articles
Bin Wang Xi’an Daxing Hospital, Department of Obstetrics and Gynecology, Xi’an, China PubMed articles Google scholar articles
Guizhi Shi Chinese Academy of Sciences, Institute of Biophysics, Beijing, China PubMed articles Google scholar articles
Dexing Zhong Xi’an Jiaotong University, School of Automation Science and Engineering, Xi’an, China PubMed articles Google scholar articles
Jianliu Wang Peking University People’s Hospital, Gynecology and Obstetrics, Beijing, China PubMed articles Google scholar articles
Qiling Li First Affiliated Hospital of Xi’an Jiaotong University, Department of Obstetrics and Gynecology, Xi’an, China PubMed articles Google scholar articles

Citation

An J, Yin P, Wang B, et al

EP142/#1526 Study on the effectiveness of using artificial intelligence image recognition system to diagnose endometrial cytopathology

International Journal of Gynecologic Cancer 2023;33:A135-A136.

Publication history

First published November 7, 2023.

Online issue publication

November 07, 2023

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