While these results are not strictly comparable as they are based on different subsets of the data, use different cross-validation strategies and report different performance metrics, they collectively show that supervised models can learn to identify patients with AD using data from elicited speech samples.
as is generally the case with supervised learning on small data sets, overfitting is a concern.