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Using machine learning approaches, we developed diagnostic models for asthenozoospermia and teratozoospermia diagnosis, with the Glmnet model showing strong performance (AUC=0.99 for asthenozoospermia, AUC=0.9997 for teratozoospermia), although these results require external validation

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During development, the pattern of DNA methylation in the genome changes as a result of a dynamic process involving both de novo DNA methylation and demethylation