Study on Toxicity of Anti-Breast Cancer Drugs Based on PSO-BP
In order to solve the problem that it is difficult to accurately predict the toxicity of drugs in the process of new drug research and development,a binary prediction model based on particle swarm optimization(PSO)opti-mized BP neural network is proposed by using computer technology.In this paper,the 20 features with the highest im-portance were selected from 729 molecular descriptors by mutual information method as independent variables and the toxicity value of drugs as dependent variables.Based on the BP neural network model,firstly,different gradient de-scent algorithms were used to calculate the accuracy of the model.It was found that the batch gradient descent algo-rithm has the best fitting effect on the BP model.Secondly,the weights and thresholds of the BP neural network model were optimally selected by using the particle swarm algorithm with dynamically variable weights,and the comparative experiments were carried out with the BP neural network,SVM and KNN model,and the results showed that the accu-racy,precision,recall and F1 value of the PSO-BP model were significantly higher than that of other models.There-fore,the PSO-BP model is an effective method to predict the toxicity of anti-breast cancer drugs.
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