NONINVASIVE DETECTION OF BLASTOCYST PLOIDY (EUPLOID VS. ANEUPLOID) USING ARTIFICIAL INTELLIGENCE (AI) WITH DEEP LEARNING METHODS-Reference-Cited by-同舟云学术

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NONINVASIVE DETECTION OF BLASTOCYST PLOIDY (EUPLOID VS. ANEUPLOID) USING ARTIFICIAL INTELLIGENCE (AI) WITH DEEP LEARNING METHODS

Published:2020-09 Issue:3 Volume:114 Page:e76
ISSN:0015-0282
Container-title:Fertility and Sterility
language:en
Short-container-title:Fertility and Sterility

Author:

Barnes Josue,Malmsten Jonas,Zhan Qiansheng,Hajirasouliha Iman,Elemento Olivier,Sierra Jose,Zaninovic Nikica,Rosenwaks Zev

Publisher

Elsevier BV

Subject

Obstetrics and Gynaecology,Reproductive Medicine

Cited by 11 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Bioengineering: a promising approach for standardization and automation of assisted reproductive technology;F&S Reviews;2024-01

2. Association between a morphokinetic ploidy prediction model risk score and miscarriage and live birth: a multicentre cohort study;Fertility and Sterility;2023-10

3. Knowledge-embedded spatio-temporal analysis for euploidy embryos identification in couples with chromosomal rearrangements;Chinese Medical Journal;2023-08-28

4. Deep learning system for classification of ploidy status using time-lapse videos;F&S Science;2023-08

5. Embryo ploidy status classification through computer-assisted morphology assessment;AJOG Global Reports;2023-08

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