Machine learning can easily produce false positives when the test set is wrongly used. Just et al in
@NatureHumBehav suggested that ML can identify suicidal ideation extremely well from fMRI and we were skeptical. Today retraction and our analysis of what went wrong came out.

Here is the retracted paper: https://nature.com/articles/s41562-017-0234-y and here is our refutation https://nature.com/articles/s41562-023-01560-6. If true, the paper's approach could revolutionize psychiatric approaches to suicide.

So what went wrong? The authors apparently used the test data to select features. Obvious mistake. A reminder for everyone into ML: never use the test set for *anything* but testing. Only practical way to do so in medicine? Lock away the test set till algorithm is registered.

Side note: it took 3 years to go through the process of demonstrating that the paper went wrong. Journals need procedures to accelerate this. Also, all the good things of this were by
@tdverstynen