Table 2 AUC values of machine learning models for distinguishing asthenozoospermia and teratozoospermia from normozoospermia.
Learner algorithm | Asthenozoospermia vs. Normozoospermia | Teratozoospermia vs. Normozoospermia |
|---|---|---|
AUC value (95% CI) | AUC value (95% CI) | |
Glmnet | 0.9871 (0.9572, 1) | 0.9997 (1, 1) |
kNN | 0.9713 (0.9194, 1) | 0.9839 (0.9444, 1) |
LDA | 0.9599 (0.8909, 1) | 0.9901 (0.9505, 1) |
Log reg | 0.6196 (0.4071, 0.8255) | 0.6272 (0.4189, 0.8496) |
Naïve Bayes | 0.9005 (0.8185, 0.9694) | 0.9198 (0.8367, 0.9839) |
nnet | 0.9604 (0.8822, 1) | 0.9871 (0.9342, 1) |
SVM | 0.9812 (0.9419, 1) | 0.9962 (0.9839, 1) |
XGBoost | 0.9147 (0.8249, 0.9754) | 0.9806 (0.9474, 1) |
Random Forest | 0.9798 (0.9483, 1) | 0.9989 (0.9929, 1) |
