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Fig. 1 | Journal of Ovarian Research

Fig. 1

From: A novel machine-learning framework based on early embryo morphokinetics identifies a feature signature associated with blastocyst development

Fig. 1

(A) Pie chart showing the distribution of the 575 embryos: embryos progressed to the expanded blastocyst stage on day 5 (BL, blue) or not (nBL, orange). (B) Scatter plot obtained from a dimensionality reduction technique (principal component analysis) considering all 575 embryos and all variables. The color of the embryos identifies those grown to the expanded blastocyst stage on day 5 (BL, blue) or not (nBL, orange). (C) Split violin plots of the distribution of the z-score of the value of all features distinguishing embryos grown to the expanded blastocyst stage on day 5 (BL, blue) or not (nBL, orange). Each violin plot is divided in half allowing for a clear observation of differences in the distribution of values between the BL and nBL groups. The p-values expressed by a significance code are computed by a Kruskal-Wallis rank sum test

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