Prediction On Vertical Craniofacial Bone In Patients With Skeletal Class ? Malocclusion Based On Genetic Algorithms Method

Objective:To establish the quantitative relation equation of the craniofacial vertical points in skeletal class ? patients with various vertical types by using Genetic Algorithms,and express the different gender by the same formula.Methods:A total of 155 skeletal class ? untreated patients,aged from 10 to 18 years old.The high-angle(A)group of 50 subjects:13.7±2.4 years old.The average-angle(B)group of 58 subjects:13.2±2.5 years old.The low-angle(C)group of 47 subjects:13.4±2.8 years old;in each group of three groups,5 samples were randomly selected for the test samples,the rest for the experimental sample.Coben,Steiner & Tween were used to measure the cephalometric radiographs.The results were analyzed by two independent samples t-test,one-way ANOVA and stepwise regression analysis to find the relevant influencing factors of craniofacial structure.The Genetic Algorithms was used to optimize the equation parameters to obtain the correlation equation.The error between the predicted value and the measured value was compared.Results:1.SPSS analysis showed that the same type of different projects for related to gender of craniofacial vertical had no statistical difference(P>0.05).2.A,B,C three groups used the one-way ANOVA,between two groups compared by the SNK-q test,showed that cranial facial vertical had statistical difference(P<0.05).3.Stepwise regression analysis was used to identify the impact factors for A,B,C three groups.4.Established the the quantitative relation equation of the craniofacial vertical points in skeletal class ? patients with various vertical types by using genetic algorithms.5.To compare with the measured value,the GAS method error is small,high precision,no statistical significance(P>0.05).Conclusion:1.There was no significant difference in craniofacial vertical for the same type different genders.2.There was significant difference in craniofacial vertical for the different vertical types.3.There was significant difference in craniofacial vertical for the same vertical types.4.Using the GAS to establish the quantitative relationship equation of he craniofacial vertical points in skeletal class ? patients with various vertical types which directly showed the vertical quantitative relationship and predicted the growth to a certain degree.