Glycosylation-Related Genes Predict the Prognosis and Immune Fraction of Ovarian Cancer Patients Based on Weighted Gene Coexpression Network Analysis (WGCNA) and Machine Learning

Figure 4

Estimation of model effectiveness and a nomogram prediction. (a) Different stratifications of clinical phenotypes in the high- and low-risk groups. (b) Connections among risk subtypes, vital status, and age stratifications. (c, d) Principal component analysis and -distribution stochastic neighbor embedding for sample discrimination in the first two dimensions. (e) Nomogram for 1-, 3-, and 5-year overall survival prediction. The red line shows an example of how to predict the prognosis. (f, g) DCA of 1-year and 3-year survival probability. The upper lines indicate more net benefit (, , and ).

(a)

(b)

(c)

(d)

(e)

(f)

(g)