In this study, functional connection strength was used to explore the hemispheric asymmetry in AD so that it can serve the AD aided diagnosis and improve the classification accuracy.ADNI database was used to verify the idea we proposed.The symmetric brain template was made to construct hemisphere brain networks, then the functional connection strength and laterality index were calculated.By using statistical analysis, the features for AD aided diagnosis were screened.According to the features, the feature space was made and the classification model was trained with SVM classifier.Importantly, the classification accuracy was improved to 89.17%, sensitivity to 90.28%and specificity to 88.24%.In conclusion, the laterality index was helpful for classification.