A software ecosystem for brain tractometry processing, analysis, and insight
Fig 5
Performance of all brain age models increases with the number of subjects in the training set.
(a) PCR Lasso, the linear baseline model starts at a relatively high R2, even at the smallest sample used here, and then increases from there. (b) MLP4, a fully connected algorithm has a similar learning curve, but it starts at much lower R2, (c) Convolutional neural networks (CNNs) start at an even lower R2 with small sample sizes, but increase precipitously reaching higher levels of performance at large sample sizes. (d) Recurrent Neural Networks (RNNs) have a variety of different performance characteristics, but are also overall very data hungry.