Currently, most assisted reproduction units transfer a single embryo to avoid multiple
pregnancies. Embryologists must select the embryo to be transferred from a cohort produced …

Objective To identify clinical decision support algorithms (CDSA) proposed for assisted
reproductive technologies (ART) and to evaluate their effectiveness in improving ART cycles …

Introduction IVF is a widely-used assisted reproductive technology with a consistent success
rate of around 30%, and improving this rate is crucial due to emotional, financial, and health …

This study aimed to assess the performance of an artificial intelligence (AI) model for
predicting clinical pregnancy using enhanced inner cell mass (ICM) and trophectoderm (TE) …

Abstract In clinical In-Vitro Fertilization (IVF), identifying the most viable embryo for transfer is
important to increasing the likelihood of a successful pregnancy. Traditionally, this process …

This paper reports, for the first time, automated grading of human blastocysts (day-5
embryos) from multi-focus images. Based on a novel attention module, a convolutional …

Within the medical field of human assisted reproductive technology, a method for
interpretable, non-invasive, and objective oocyte evaluation is lacking. To address this …

Background Blastocyst morphology has been demonstrated to be associated with ploidy
status. Existing artificial intelligence models use manual grading or 2D images as the input …

Background Data sciences and artificial intelligence are becoming encouraging tools in
assisted reproduction, favored by time-lapse technology incubators. Our objective is to …

In vitro fertilization (IVF) has revolutionized infertility treatment, benefiting millions of couples
worldwide. However, current clinical practices for embryo selection rely heavily on visual …