most citedSystematic Misestimation of Machine Learning Performance in Neuroimaging Studies of Depression

118 citations · 165 across the 6 of their papers we have counts for

collaborators

6 papers

q-bio.NC2021★ 7 cited

More Alike than Different: Quantifying Deviations of Brain Structure and Function in Major Depressive Disorder across Neuroimaging Modalities

Nils R. Winter, Ramona Leenings, Jan Ernsting +28

Introduction: Identifying neurobiological differences between patients suffering from Major Depressive Disorder (MDD) and healthy individuals has been a mainstay of clinical neuros…

eess.SY2021★ 6 cited

Towards a Network Control Theory of Electroconvulsive Therapy Response

Tim Hahn, Hamidreza Jamalabadi, Erfan Nozari +24

Electroconvulsive Therapy (ECT) is arguably the most effective intervention for treatment-resistant depression. While large interindividual variability exists, a theory capable of…

cs.LG2021★ 1 cited

An Uncertainty-Aware, Shareable and Transparent Neural Network Architecture for Brain-Age Modeling

Tim Hahn, Jan Ernsting, Nils R. Winter +31

The deviation between chronological age and age predicted from neuroimaging data has been identified as a sensitive risk-marker of cross-disorder brain changes, growing into a corn…

eess.IV2021★ 9 cited

Predicting brain-age from raw T 1 -weighted Magnetic Resonance Imaging data using 3D Convolutional Neural Networks

Lukas Fisch, Jan Ernsting, Nils R. Winter +33

Age prediction based on Magnetic Resonance Imaging (MRI) data of the brain is a biomarker to quantify the progress of brain diseases and aging. Current approaches rely on preparing…

q-bio.NC2019★ 118 cited

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…

q-bio.NC2019★ 24 cited

Biological sex classification with structural MRI data shows increased misclassification in transgender women

Claas Flint, Katharina Förster, Sophie A. Koser +16

Transgender individuals (TIs) show brain structural alterations that differ from their biological sex as well as their perceived gender. To substantiate evidence that the brain str…