In the Department of Machine Learning, we develop models to improve decision making in clinical brain research.
01
Schulz, M.A., Bzdok, D., Haufe, S., Haynes, J.D., Ritter, K.
Performance reserves in brain-imaging-based phenotype prediction
02
Schulz, M.A., Hetzer, S., Eitel, F., Asseyer, S., Meyer-Arndt, L., Schmitz-Hübsch, T., et al
Similar neural pathways link psychological stress and brain-age in health and multiple sclerosis
03
Vorisek, C., Stellmach, C., Mayer, P., Klopfenstein, S., Bures, D., Diehl, A., Henningsen, M., Ritter, K., Thun, S.
Artificial Intelligence Bias in Health Care: Web-Based Survey
04
Klingenberg, M., Stark, D., Eitel, F. et al
Higher performance for women than men in MRI-based Alzheimer’s disease detection
05
Wang, D., Honnorat, N., Fox, P. T., Ritter, K., Eickhoff, S. B., Seshadri, S., ... & Alzheimer’s Disease Neuroimaging Initiative
Deep neural network heatmaps capture Alzheimer’s disease patterns reported in a large meta-analysis of neuroimaging studies
06
Brandt, L., Ritter, K., Schneider-Thoma, J., Siafis, S., Montag, C., Ayrilmaz, H. et al
Predicting psychotic relapse following randomised discontinuation of paliperidone in individuals with schizophrenia or schizoaffective disorder: an individual participant data analysis
07
Fast, L., Temuulen, U., Villringer, K., Kufner, A., Ali, H.F., Siebert, E., Huo, S et al
Machine learning-based prediction of clinical outcomes after first-ever ischemic stroke
08
Rane, R. P., Musial, M. P. M., Beck, A., Rapp, M., Schlagenhauf, F., Banaschewski, T., ... & IMAGEN consortium
Uncontrolled eating and sensation-seeking partially explain the prediction of future binge drinking from adolescent brain structure
09
Schulz, M. A., Koch, A., Guarino, V. E., Kainmueller, D., & Ritter, K
Data augmentation via partial nonlinear registration for brain-age prediction
10
Chien, C., Seiler, M., Eitel, F., Schmitz-Hübsch, T., Paul, F., & Ritter, K.
Prediction of high and low disease activity in early MS patients using multiple kernel learning identifies importance of lateral ventricle intensity
11
Rane, R. P., de Man, E. F., Kim, J., Görgen, K., Tschorn, M., Rapp, M. A., ... & IMAGEN consortium.
Structural differences in adolescent brains can predict alcohol misuse
12
Subramaniam, P., Kossen, T., Ritter, K., Hennemuth, A., Hildebrand, K., Hilbert, A., ... & Madai, V. I.
Generating 3D TOF-MRA volumes and segmentation labels using generative adversarial networks
13
Rane, R. P., Heinz, A., & Ritter, K
AIM in Alcohol and Drug Dependence
14
Brasanac, J., Ramien, C., Gamradt, S., Taenzer, A., Glau, L., Ritter, K. et al
Immune signature of multiple sclerosis-associated depression
15
Kübler, D., Wellmann, S. K., Kaminski, J., Skowronek, C., Schneider, G. H., Neumann, W. J., ... & Kühn, A.
Nucleus basalis of Meynert predicts cognition after deep brain stimulation in Parkinson's disease
16
Eitel, F., Albrecht, J. P., Weygandt, M., Paul, F., & Ritter, K.