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Fig. 3 | Journal of Ovarian Research

Fig. 3

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

Fig. 3

(A) Correlation graph of the selected rules. Vertices represent the rules and arcs are reported only for a correlation value > 0.8 (computed by Matthews Correlation Coefficient (MCC). (B) Line plot representing the ability of different combinations of classifiers to classify the expanded or not expanded blastocyst stage. Each dot corresponds to the AUC computed using a different number of rules in input. (C) Set of 6 rules of the feature-signature with (D) their composition in terms of variable category

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