| 黄鹏,谭红专,周立波,奉水东.支持向量机在洪灾区创伤性应激障碍预测中的应用[J].Chinese journal of Epidemiology,2009,30(1):78-81 |
| 支持向量机在洪灾区创伤性应激障碍预测中的应用 |
| The application of Support Vector Machine for prediction of posttraumatic stress disorder on adults in flood district |
| Received:July 23, 2008 |
| DOI： |
| KeyWord: 洪灾 创伤性应激障碍 预测 支持向量机 |
| English Key Word: Flood Posttraumatic stress disorder Prediction Support Vector Machine |
| FundProject:美国中华医学基金会资助项(CMB98-689) |
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| Abstract: |
| 应用支持向量机对洪灾区居民创伤性应激障碍(PTSD)的发生进行预测.使用美国<精神障碍的诊断统计手册>第四版(DSM-IV)中关于PTSD的诊断标准对洪灾区成年人进行评定,以是否发生PTSD为应变量,以影响PTSD发生的23个因素为自变量,建立基于支持向量机(SVM)的预测模型,对遭受洪灾后PTSD的发生进行预测.将影响PTSD发生的23个因素纳入预测模型后,测试集SVM分类与实际类别的一致率为88.05%,灵敏度为75.0%,特异度为89.4%.结论:应用SVM建立预测模型对于洪灾区PTSD发生的预测具有较好的效果,被纳入的23个因素作为输入向量有良好的预测效率. |
| English Abstract: |
| To predict the occurrence ofposttraumatic stress disorder (PTSD),using a Support Vector Machine (SVM) on adults in flood district.Diagnostic and Statistical Manuals on Mental Disorders (IV Edition) were used to examine and diagnose the victims in flood districts.Based on the forecasting model of SVM with PTSD as dependent variables and 23 influence factors of PTSD as independent variables,prediction of PTSD was conducted among the victims.After considering 23 influence factors into the prediction model,the agreement rate of prediction of the model was 88.05 percent,with sensitivity as 75.0 percent,and specificity as 89.4percent.Conclusion: The prediction model based on SVM with 23 influence factors had good effect on predicting the occurrence of PTSD. |
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