In the Department of Machine Learning, we develop models to improve decision making in clinical brain research.

01
Hilbert, K., Weller, P., Ritter, K., Haynes, J.D., Walter, H., Lueken, U.

Design studies for clinical prediction

Aug 08, 2024 | Science
03
Noteboom, S., Seiler, M., Chien, C., Rane, R. P., Barkhof, F., Strijbis, E.M.M,...& Ritter, K.

Evaluation of machine learning-based classification of clinical impairment and prediction of clinical worsening in multiple sclerosis

Jun 23, 2024 | Journal of Neurology
04
Schulz, M.A., Albrecht, J.P., Yilmaz, A., Koch, A., Kainmüller, D., Leser, U. & Ritter, K.

TLIMB-a transfer learning framework for image analysis of the brain

Mar 25, 2024 | CEUR Workshop Proceedings
05
Mitrovska, A., Safari, P., Ritter, K., Shariati, B., Fischer, J. K.

Secure federated learning for Alzheimer's disease detection

Mar 07, 2024 | Frontiers in Aging Neuroscience
06
Oliveira, M., Wilming, R., Clark, B., Budding, C., Eitel, F., Ritter, K., Haufe, S.

Benchmarking the influence of pre-training on explanation performance in MR image classification

Feb 24, 2024 | Frontiers in Artificial Intelligence
07
Schulz, M.A., Bzdok, D., Haufe, S., Haynes, J.D., Ritter, K.

Performance reserves in brain-imaging-based phenotype prediction

Jan 23, 2024 | Cell Reports
08
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

Sep 15, 2023 | Iscience
09
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

Jun 22, 2023 | Journal of Medical Internet Research
10
Klingenberg, M., Stark, D., Eitel, F. et al

Higher performance for women than men in MRI-based Alzheimer’s disease detection

Apr 20, 2023 | Alzheimer's Research & Therapy
11
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

Apr 01, 2023 | NeuroImage
12
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

Mar 01, 2023 | The Lancet Psychiatry
13
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

Feb 21, 2023 | Frontiers in neurology
14
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

Jan 01, 2023 | NeuroImage: Clinical
15
Schulz, M. A., Koch, A., Guarino, V. E., Kainmueller, D., & Ritter, K

Data augmentation via partial nonlinear registration for brain-age prediction

Oct 06, 2022 | International Workshop on Machine Learning in Clinical Neuroimaging