{"title":"FertilitY Predictor-a machine learning-based web tool for the prediction of assisted reproduction outcomes in men with Y chromosome microdeletions.","authors":"Stacy Colaco, Priyanka Narad, Ajit Kumar Singh, Payal Gupta, Alakto Choudhury, Abhishek Sengupta, Deepak Modi","doi":"10.1007/s10815-024-03338-9","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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 .</p><p><strong>Conclusions: </strong>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.</p><p><strong>Trial registration: </strong>PROSPERO (CRD42022311738).</p>","PeriodicalId":15246,"journal":{"name":"Journal of Assisted Reproduction and Genetics","volume":" ","pages":"473-481"},"PeriodicalIF":3.2000,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11871245/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Assisted Reproduction and Genetics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s10815-024-03338-9","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/12/9 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
引用次数: 0
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.
期刊介绍：
The Journal of Assisted Reproduction and Genetics publishes cellular, molecular, genetic, and epigenetic discoveries advancing our understanding of the biology and underlying mechanisms from gametogenesis to offspring health. Special emphasis is placed on the practice and evolution of assisted reproduction technologies (ARTs) with reference to the diagnosis and management of diseases affecting fertility. Our goal is to educate our readership in the translation of basic and clinical discoveries made from human or relevant animal models to the safe and efficacious practice of human ARTs. The scientific rigor and ethical standards embraced by the JARG editorial team ensures a broad international base of expertise guiding the marriage of contemporary clinical research paradigms with basic science discovery. JARG publishes original papers, minireviews, case reports, and opinion pieces often combined into special topic issues that will educate clinicians and scientists with interests in the mechanisms of human development that bear on the treatment of infertility and emerging innovations in human ARTs. The guiding principles of male and female reproductive health impacting pre- and post-conceptional viability and developmental potential are emphasized within the purview of human reproductive health in current and future generations of our species.
The journal is published in cooperation with the American Society for Reproductive Medicine, an organization of more than 8,000 physicians, researchers, nurses, technicians and other professionals dedicated to advancing knowledge and expertise in reproductive biology.
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