7 citations · 7 across the 1 of their papers we have counts for
3 papers
Multi-site benchmark classification of major depressive disorder using machine learning on cortical and subcortical measures
Vladimir Belov, Tracy Erwin-Grabner, Ali Saffet Gonul +63
Machine learning (ML) techniques have gained popularity in the neuroimaging field due to their potential for classifying neuropsychiatric disorders. However, the diagnostic predict…
Systematic Misestimation of Machine Learning Performance in Neuroimaging Studies of Depression
Claas Flint, Micah Cearns, Nils Opel +15
We currently observe a disconcerting phenomenon in machine learning studies in psychiatry: While we would expect larger samples to yield better results due to the availability of m…
The lure of misleading causal statements in functional connectivity research
David Marc Anton Mehler, Konrad Paul Kording
As neuroscientists we want to understand how causal interactions or mechanisms within the brain give rise to perception, cognition, and behavior. It is typical to estimate interact…