From: Machine learning approach for the detection of vitamin D level: a comparative study
Predictors | \(G\) | P value | Predictors | \(G\) | P value |
---|---|---|---|---|---|
Gender | 0.102 | 0.563 | TRY | -0.520 |  < 0.001 |
Age groups | 0.203 |  < 0.001 | MtS | -0.719 |  < 0.001 |
SBP | -0.130 | 0.105 | Having alcohol | -0.135 | 0.070 |
DBP | -0.150 | 0.088 | Having smoke | -0.102 | 0.201 |
FBS | -0.049 | 0.560 | Skin Tone | -0.414 |  < 0.001 |
HOMA-IR | 0.027 | 0.735 | Usage of sun protection cream | -0.121 | 0.203 |
hs-CRP | -0.488 | < 0.001 | Sunlight exposure status | 0.372 | 0.007 |
UAL | -0.438 |  < 0.001 | Usage of MMS | 0.210 |  < 0.001 |
HDL | 0.453 |  < 0.001 | Usage of FOS | 0.247 |  < 0.001 |
TCL | 0.132 | 0.101 | WC | -0.487 |  < 0.001 |
LDL | 0.068 | 0.375 | BMI | -0.602 |  < 0.001 |