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Convolutional neural network using magnetic resonance brain imaging to predict outcome from tuberculosis meningitis

Table 5

Performances of the non-imaging, imaging-only, and fused model on test set (N=56), stratified by HIV status. For each type of model, the performance metrics (AUC and IPA) and their variation were estimated based on n=10 models optimised on n=10 folds.

Table 5

doi: https://doi.org/10.1371/journal.pone.0321655.t005