Abstract
An evidence-based algorithm for the probability of predicting successful live birth has significant clinical utility in counseling infertility patients regarding embryo transfer outcomes. Towards this objective, we examined an artificial intelligence (AI), machine learning classification model using patient clinical measurements and IVF cycle characteristics to assess the prognostic value in estimating treatment outcomes including live birth.
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