Fig. 2 | Scientific Reports

Fig. 2

From: Machine learning based differential diagnosis of SAPHO syndrome and secondary bone tumors using whole body bone scintigraphy

Fig. 2

(A) In the training set and test set of G1 dataset, the model ROC AUC and RF model after manually managing (0.938 and 0.939) filtered features are similar, and both are higher than LR model (0.934 and 0.929). (B) We use radar plots to display the normalized evaluation parameters. The comprehensive evaluation indicators of the manual management group such as accuracy (88.274%), precision (88.675%), recall (88.274%), f1-score (0.882), etc. have further improved.

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