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生育力预测器——一种基于机器学习的网络工具,用于预测Y染色体微缺失男性的辅助生殖结局。

FertilitY Predictor-a machine learning-based web tool for the prediction of assisted reproduction outcomes in men with Y chromosome microdeletions.

作者信息

Colaco Stacy, Narad Priyanka, Singh Ajit Kumar, Gupta Payal, Choudhury Alakto, Sengupta Abhishek, Modi Deepak

机构信息

Molecular and Cellular Biology Laboratory, ICMR-National Institute for Research in Reproductive and Child Health, JM Street, Parel, Mumbai, Maharashtra, 400012, India.

Division of Development Research, Indian Council of Medical Research, Ansari Nagar, New Delhi, India.

出版信息

J Assist Reprod Genet. 2025 Feb;42(2):473-481. doi: 10.1007/s10815-024-03338-9. Epub 2024 Dec 9.

Abstract

PURPOSE

Y chromosome microdeletions (YCMD) are a common cause of azoospermia and oligozoospermia in men. Herein, we developed a machine learning-based web tool to predict sperm retrieval rates and success rates of assisted reproduction (ART) in men with YCMD.

METHODS

Data on ART outcomes of men with YCMD who underwent ART were extracted from published studies by performing a systematic review. This data was used to develop a web-based predictive algorithm using machine learning.

RESULTS

FertilitY Predictor classifies the type of YCMD into AZFa, AZFb, AZFc, their combinations, and gr/gr deletions based on the genetic markers as input. Further, it predicts the probability of sperm retrieval, fertilization rate, clinical pregnancy rate, and live birth rate based on the type of YCMD. Validation studies demonstrated its high accuracy and predictability for sperm retrieval, clinical pregnancy rates, and live birth rates. The tool predicts that men with deletions have a chance of sperm retrieval that varies with type of deletions, the clinical pregnancy rates and live birth rates are lower in men with AZF deletions. A trial version of the tool is available at http://fertilitypredictor.sbdaresearch.in .

CONCLUSIONS

FertilitY Predictor allows users to classify AZFa, AZFb, AZFc, and gr/gr deletions and also predict the outcomes of ART based on the type of deletions.

TRIAL REGISTRATION

PROSPERO (CRD42022311738).

摘要

目的

Y染色体微缺失(YCMD)是男性无精子症和少精子症的常见原因。在此,我们开发了一种基于机器学习的网络工具,用于预测患有YCMD的男性的精子获取率和辅助生殖(ART)成功率。

方法

通过系统评价,从已发表的研究中提取接受ART的患有YCMD的男性的ART结果数据。这些数据用于使用机器学习开发基于网络的预测算法。

结果

FertilitY Predictor根据输入的遗传标记将YCMD的类型分为AZFa、AZFb、AZFc、它们的组合以及gr/gr缺失。此外,它根据YCMD的类型预测精子获取的概率、受精率、临床妊娠率和活产率。验证研究证明了其在精子获取、临床妊娠率和活产率方面的高准确性和可预测性。该工具预测,有缺失的男性有精子获取的机会,其机会因缺失类型而异,AZF缺失的男性临床妊娠率和活产率较低。该工具的试用版可在http://fertilitypredictor.sbdaresearch.in获取。

结论

FertilitY Predictor允许用户对AZFa、AZFb、AZFc和gr/gr缺失进行分类,并根据缺失类型预测ART的结果。

试验注册

PROSPERO(CRD42022311738)。

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