  For many psychiatric disorders, neuroimaging offers a potential for
revolutionizing diagnosis and treatment by providing access to preverbal mental
processes. In their study "Machine learning of neural representations of
suicide and emotion concepts identifies suicidal youth."1, Just and colleagues
report that a Naive Bayes classifier, trained on voxelwise fMRI responses in
human participants during the presentation of words and concepts related to
mortality, can predict whether an individual had reported having suicidal
ideations with a classification accuracy of 91%. Here we report a reappraisal
of the methods employed by the authors, including re-analysis of the same data
set, that calls into question the accuracy of the authors findings.
