In the Department of Machine Learning, we develop models to improve decision making in clinical brain research.
01
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
02
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
03
Klingenberg, M., Stark, D., Eitel, F. et al
Higher performance for women than men in MRI-based Alzheimer’s disease detection
04
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
05
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
06
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
07
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
08
Schulz, M. A., Koch, A., Guarino, V. E., Kainmueller, D., & Ritter, K
Data augmentation via partial nonlinear registration for brain-age prediction
09
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
10
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
11
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
12
Rane, R. P., Heinz, A., & Ritter, K
AIM in Alcohol and Drug Dependence
13
Brasanac, J., Ramien, C., Gamradt, S., Taenzer, A., Glau, L., Ritter, K. et al
Immune signature of multiple sclerosis-associated depression
14
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
15
Eitel, F., Albrecht, J. P., Weygandt, M., Paul, F., & Ritter, K.
Patch individual filter layers in CNNs to harness the spatial homogeneity of neuroimaging data
16
Schulz, M. A., Baier, S., Timmermann, B., Bzdok, D., & Witt, K.