A Diagnosis Model of Poisoning Based on BP Neural Network

Objective:To observe the effect of the diagnosis model of poisoning based on BP neural network.Methods:41 poisoning cases were selected to be the original data,after the attributes reduction with the rough set algorithm,and the cases were divided into training set and test set.Learning from the training set,the diagnosis model based on BP neural network was established.Results:The model was used to diagnose the test set,and the correct rate was 87.5%.Conclusion:The model can aid doctors or experts in forensic medicine in the practice of poisoning diagnosis and is proved to be reasonable.