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Research Article | Open Access

An artificial intelligence model for embryo selection in preimplantation DNA methylation screening in assisted reproductive technology

Jianhong Zhan1,( )Chuangqi Chen2,Na Zhang3,Shuhuai Zhong4Jiaming Wang1,5,6Jinzhou Hu1,5Jiang Liu1,5,6( )
Institute of Biophysics, Chinese Academy of Science, Beijing 100101, China
Guangdong Women's and Children's Hospital, Guangzhou 511400, China
Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing Maternal and Child Health Care Hospital, Beijing 100026, China
Dongguan People’s Hospital, Dongguan 523059, China
University of the Chinese Academy of Science, Beijing 101408, China
School of Future Technology, University of the Chinese Academy of Science, Beijing 100049, China

Jianhong Zhan, Chuangqi Chen and Na Zhang contributed equally to this work.

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Graphical Abstract

Abstract

Embryo quality is a critical determinant of clinical outcomes in assisted reproductive technology (ART). A recent clinical trial investigating preimplantation DNA methylation screening (PIMS) revealed that whole genome DNA methylation level is a novel biomarker for assessing ART embryo quality. Here, we reinforced and estimated the clinical efficacy of PIMS. We introduce PIMS-AI, an innovative artificial intelligence (AI) based model, to predict the probability of an embryo producing live birth and subsequently assist ART embryo selection. Our model demonstrated robust performance, achieving an area under the curve (AUC) of 0.90 in cross-validation and 0.80 in independent testing. In simulated embryo selection, PIMS-AI attained an accuracy of 81% in identifying viable embryos for patients. Notably, PIMS-AI offers significant advantages over conventional preimplantation genetic testing for aneuploidy (PGT-A), including enhanced embryo discriminability and the potential to benefit a broader patient population. In conclusion, our approach holds substantial promise for clinical application and has the potential to significantly improve the ART success rate.

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Biophysics Reports
Pages 352-361
Cite this article:
Zhan J, Chen C, Zhang N, et al. An artificial intelligence model for embryo selection in preimplantation DNA methylation screening in assisted reproductive technology. Biophysics Reports, 2023, 9(6): 352-361. https://doi.org/10.52601/bpr.2023.230035

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Received: 11 November 2023
Accepted: 28 November 2023
Published: 31 December 2023
© The Author(s) 2023

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