## 3 Results  
Figure 2 shows the prediction results for efficacy models of four metabolic risk factors. In the experiments using a combination of variables selected from different variable sets, the AUC values for efficacy models of four metabolic risk factors ranged from 0.54 to 0.785. The efficacy model of the HDL cholesterol level showed the best AUC value among the four models (AUC = 0.785 (confidence interval = 0.693, 0.877)). The AUC value of the efficacy model of triglyceride level was 0.659 (0.551, 0.768), while the efficacy model of DBP showed an AUC value of 0.665 (0.551, 0.78) and the efficacy model of SBP indicated the lowest AUC value (AUC = 0.54 (0.385, 0.694)). Selected variables for the efficacy model differed according to the four metabolic risk factors. All variables selected by LASSO variable selection in each model of efficacy prediction are described in Table 3. Specifically, most of the included variables in each model for efficacy prediction showed a difference before and after treatment (namely, the difference according to efficacy response to oral administration). The efficacy model of triglyceride level included 5 variables. R83_84 was more strongly associated with the efficacy response to treatment (\(p\) = 0.006, odds ratio (OR) = 3.01 (1.37, 6.61), and AUC = 0.64 (0.53, 0.75)) than other indices within this model, and Q23, FHD_25_125_53_153, and sMFCC4 were associated with efficacy response (\(p\) = 0.016 and AUC = 0.48 (0.35, 0.60); \(p\) = 0.03, OR = 0.62 (0.40, 0.95), and AUC = 0.58 (0.47, 0.69); \(p\) = 0.031, OR = 1.6 (1.04, 2.45), and AUC = 0.61 (0.49, 0.72)). The efficacy model of HDL included 10 variables. Among these variables, Q5 and Q6 were more strongly associated with the efficacy response than other indices within the model (\(p\) = 0.003 and AUC = 0.53 (0.41, 0.65); \(p\) = 0.001 and AUC = 0.54 (0.41, 0.66)). Pai_72_73 and ChRD_b_avg, indicating angle and color in specific regions in the face, were highly associated with the efficacy response (\(p\) = 0.009, OR = 0.54 (0.34, 0.86), and AUC = 0.61 (0.5, 0.73); \(p\) = 0.002, OR = 2.08 (1.3, 3.35), and AUC = 0.67 (0.56, 0.78)). The efficacy model of DBP included a total of 6 variables. The Q10 variable was more strongly associated with the efficacy response than other indices included in this model (\(p\) = 0.003, AUC = 0.51 (0.38, 0.64)). In addition, the BodyCenter_a, FurCenter_a, FurRoot_a, and TotalRatio variables were highly associated with the efficacy response (\(p\) = 0.017, OR = 0.54 (0.33, 0.90), and AUC = 0.60 (0.48, 0.72); \(p\) = 0.018, OR = 0.59 (0.38, 0.91), and AUC = 0.6 (0.48, 0.72); \(p\) = 0.019, OR = 0.59 (0.38, 0.92), and AUC = 0.59 (0.47, 0.72); \(p\) = 0.01, OR = 1.83 (1.16, 2.90), and AUC = 0.61 (0.49, 0.72)). Finally, the efficacy model of SBP included 4 variables. FDV_52, 50, FVD 81_50, 94, 194 and FVD 81_51, 94, 194 were associated with the efficacy response (\(p\) = 0.031, OR = 1.83 (1.06, 3.17), and AUC = 0.61 (0.45, 0.76); \(p\) = 0.014, OR = 2.03 (1.15, 3.58), and AUC = 0.66 (0.51, 0.82); \(p\) = 0.014, OR = 2.10 (1.16, 3.80), and AUC = 0.63 (0.50, 0.77)). However, FVV_47_52_81_50 was not associated with the efficacy response in this model (\(p\) = 0.9, OR = 0.57 [0.30, 1.09], and AUC = 0.55 (0.42, 0.69)).