Moreover, the ANN method outperformed all other models with the highest Acc achieved ranging from 73 to 100%, which showed the combined proteomic and genic approaches developed to be extremely robust and capable of identifying optimal biomarker subsets (containing immune-related biomarkers cAMP, S100A9, TLR8, IL6R, HDDC3, SDC2, and APOA1, and A2M) of true importance in PCOS [66, 78–80]. The gene discussed is APOA1; the disease is polycystic ovary syndrome.