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Journal of Big Data
Fig. 2 | Journal of Big Data

Fig. 2

From: Artificial intelligence learning landscape of triple-negative breast cancer uncovers new opportunities for enhancing outcomes and immunotherapy responses

Fig. 2

Development of the MLIIC signature based on ML. (A) Venn plot shows the intersected genes identified by six ML algorithms for classification. (B) Univariate Cox regression analysis of the screened nine intersected genes displayed via forest plot. (C) Dimension reduction of the ten prognostic genes by the CoxBoost algorithm. (D) Dimension reduction of the ten prognostic genes by the LassoCox algorithm. (E) Dimension reduction of the ten prognostic genes by RSF algorithm. (F) Venn plot shows the intersected prognostic genes identified by three ML algorithms for survival. (G) Performance of 19 ML algorithms for scoring in terms of signature construction. (H) Kaplan-Meier survival curves of the MLIIC signature regarding OS in the TCGA, METABRIC, GSE96058, and GSE103091 datasets. (I) Time-dependent ROC curves of the MLIIC signature regarding 1-, 2-, 3-, 4-, and 5-year OS in the TCGA, METABRIC, GSE96058, and GSE103091 datasets

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