RESULTS: This study investigates the effect of iterations in sliding semi-landmarks and their results on the predictive ability in GM analyses of soft-tissue in 3D human face. Principal Component Analysis (PCA) is used for feature selection and the gender are predicted using Linear Discriminant Analysis (LDA) to test the effect of each relaxation state. The results show that the classification accuracy is affected by the number of iterations but not in progressive pattern. Also, there is stability at 12 relaxation state with highest accuracy of 96.43% and an unchanging decline after the 12 relaxation state.
CONCLUSIONS: The results indicate that there is a particular number of iteration or cycle where the sliding becomes optimally relaxed. This means the higher the number of iterations is not necessarily the higher the accuracy.
CASE PRESENTATION: Herein, we report a case of very severe hypertriglyceridemia 32 mmol/L (2834 mg/dL) detected incidentally at three months old in an otherwise well boy born late preterm with intrauterine growth restriction, when he presented with lipaemic plasma. He was later diagnosed with CLS. No pathogenic mutations were found for hypertriglyceridemia, and no secondary causes could explain his very severe hypertriglyceridemia.
CONCLUSIONS: The very severe hypertriglyceridemia in this case may appear to be a serious presentation of an unrecognised clinical feature of CLS, further expanding its phenotype.