Using Artificial Neural Network Model for the Sexual Offender Recidivism Prediction

• Main Authors: Chang-Cheng Liu, 劉昌誠
• Other Authors: 徐建業
• Format: Others
• Language: zh-TW
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/60957473188218040457

碩士 === 臺北醫學大學 === 醫學資訊研究所 === 98 === In Taiwan, sexual offenders need to receive professional assessments before leaving the prison, but the lack of "high recidivism risk" standard is a serious problem. This study try to use artificial neural network model to provide an important reference to forensic psychiatric professionals, thereby strengthening the predict ability, reduce errors, and saving manpower and money. Participants of this study were 552 sexual offenders released from a prison in northern Taiwan in 1995 and 1996, and we follow all cases from the time of release to December 31, 2003 and 2004 separately. 22 risk predictors with statistic significance are selected to construct a artificial neural network (ANN) model for the sexual offender recidivism prediction. Then we examined the predict ability of the ANN model by receiver operating characteristic (ROC) analysis, and compare with the model constructed by logistic regression, RRASOR, MnSOST-R, and Static-99. The area under the ROC curve for ANN model is the biggest, after comparing with all prediction models, ANN model got better predict ability.