Similarly, researchers compared different types of ML algorithms containing RF, SVM, ANN, and generalized linear model (GLM) to select the optimal model for prioritizing susceptible genes from the genome of PCOS (including CNTN2, CASR, CACNB3, MFAP2, BTBD9, TMOD1, PPM1B, CAMKK, MSL3, ALPK2, PAB23, RAB40C, AMPD3, SPARC, and CCR7) [20, 67–76]. The gene discussed is MFAP2; the disease is polycystic ovary syndrome.