Figure 1 | Scientific Reports

Figure 1

From: Prediction of xerostomia in elderly based on clinical characteristics and salivary flow rate with machine learning

Figure 1

Work flow diagrams of the study. We first find the cut-off values of UFR and SFR by using Youden’s index (A). These values are then validated by a randomly split test set. Then, with multiple input variables, classifications using various learning algorithms were performed under tenfold cross validation (B). For each algorithm, a ROC curve was obtained from the predicted logits of all ten-fold samples, which represents overall prediction performance of the algorithm.

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