Predicting a live birth by artificial intelligence incorporating both the blastocyst image and conventional embryo evaluation parameters

Figure 1 Flowchart for generating the artificial intelligence classifiers.  The artificial intelligence classifier consisted of a combination of 10 Layers of a convolutional neural network for an image and each elementwise layer often significant factors of the conventional embryo evaluation (CEE) that we had reported[14]. The ten factors chosen as independent factors to predict live birth were age, the number of embryo transfers, anti-Müllerian hormone concentration, day-3 blastomere number, grade on day 3, embryo cryopreservation day, inner cell mass, trophectoderm, average diameter, and body mass index. The functions in the elementwise layer for each factor of the CEE are shown as formulas in Table 1. The image processing and ten factors of the conventional embryo evaluation tensor were combined at the catenated layer. AI: Artificial intelligence.