Development and Internal Validation of Machine Learning Algorithms for Determining Sodium Valproate Concentrations below the Standard Level Using a Risk Prediction Model of Children with Epilepsy

<div>Development of machine learning algorithms. (a) Reverse cumulative distribution of residuals was plotted to show the residual distribution of random forest (RF), support vector machine (SVM), gradient boosting machine (GBM), generalized linear model (GLM), and neural network (NNET). (b) Boxplots of residuals were plotted to show the residual distribution of the RF, SVM, GBM, GLM, and NNET models.</div>

Journal of Clinical Pharmacy and Therapeutics

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Figure 2

Figure 2: Development and Internal Validation of Machine Learning Algorithms for Determining Sodium Valproate Concentrations below the Standard Level Using a Risk Prediction Model of Children with Epilepsy 

Figure 2 | Development and Internal Validation of Machine Learning Algorithms for Determining Sodium Valproate Concentrations below the Standard Level Using a Risk Prediction Model of Children with Epilepsy 