Skip to main content
Fig. 4 | Human Genomics

Fig. 4

From: Pharmacovariome scanning using whole pharmacogene resequencing coupled with deep computational analysis and machine learning for clinical pharmacogenomics

Fig. 4

The comparison of average accuracy for the designed ML model by means of both internal and external cross-validation. Accuracy of the prediction model for developing ADRs in cardiovascular patients demonstrated by different cross-validation approaches. A The RFE process of machine learning reduced the variables to 175 important genotype variants. These are the final variants indicated by the RF model, which employed internal fivefold cross-validation. B The accuracy changed during the testing of the designed model by external cross-validation and the number of important pharmacovariants reduced to 60. The subset of the variants achieved an average accuracy of 0.9818 and 0.9512 on predicting whether a patient will have ADRs or not, respectively. ML: machine learning, ADR: adverse drug reactions, RFE: recursive feature elimination, RF: random forest

Back to article page

Human Genomics

ISSN: 1479-7364