Application of Neural Network Algorithms to Implement Drug Abuse Research on Identifying Cannabis Use Disorder through Analysing Personality Traits

Abstract

Frequent cannabis use will certainly lead to a reasonable mental complication. Daily and long-time period cannabis use is associated with more intellectual loss. This is identified as cannabis use disorder (CUD). The CUD starting at the teen age is the strongest predictors of cognitive impairment. However, it's miles uncertain which comes first. Whether CUD results in early onset cannabis use or cannabisearly use in lives reasons the CUD. The aim of this paper is to investigate the most influential features origins the CUD among the cannabis user’s personality trails. Depending on the self-extracted data collected from 1885 individuals three of the NN models were built. These three NN models apply the 10-Fold cross validation and 30-70 Hold-Out validation methods to provide the reliability of the prediction results. Among the three methods the RNN Hold-Out method achieves 99.19% as best accuracy result.