We can observe a clear trend, where models trained on sMRI features have the lowest performance with an average accuracy of 62% and AUC of 0.65, while models trained on fMRI features achieved an average accuracy of 67% and AUC of 0.72.
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A Framework for Comparison and Interpretation of Machine Learning Classifiers to Predict Autism on the ABIDE Dataset.
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