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]. This evidence concerns the gene RAB40C and polycystic ovary syndrome.