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Artificial Intelligence in the Assessment of Female Reproductive Function Using Ultrasound A Review

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成果类型:
期刊论文
作者:
Chen, Zhiyi;Wang, Ziyao;Du, Meng;Liu, Zhenyu
通讯作者:
Zhiyi Chen
作者机构:
[Wang, Ziyao; Liu, Zhenyu; Chen, Zhiyi] Univ South China, Affiliated Hosp 1, Med Imaging Ctr, Hengyang Med Sch, 69 Chuanshan Rd, Hengyang 421001, Peoples R China.
[Du, Meng; Chen, Zhiyi] Univ South China, Inst Med Imaging, Hengyang, Peoples R China.
通讯机构:
[Zhiyi Chen ] T
The First Affiliated Hospital, Medical Imaging Center, Hengyang Medical School, University of South China, Hengyang, China<&wdkj&>Institute of Medical Imaging, University of South China, Hengyang, China
语种:
英文
关键词:
artificial intelligence;endometrial receptivity;infertility;ovarian response;ultrasound
期刊:
Journal of Ultrasound in Medicine
ISSN:
0278-4297
年:
2022
卷:
41
期:
6
页码:
1343-1353
基金类别:
National Key R&D Program of China [2019YFE0110400]; Clinical Research 4310 Program of the First Affiliated Hospital of The University of South China [4310-2021-K06]
机构署名:
本校为第一机构
摘要:
The incidence of infertility is continuously increasing nearly all over the world in recent years, and novel methods for accurate assessment are of great need. Artificial Intelligence (AI) has gradually become an effective supplementary method for the assessment of female reproductive function. It has been used in clinical follicular monitoring, optimum timing for transplantation, and prediction of pregnancy outcome. Some literatures summarize the use of AI in this field, but few of them focus on the assessment of female reproductive function by AI-aided ultrasound. In this review, we mainly d...

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