| Layer-wise relevance propagation for explaining deep neural network decisions in MRI-based Alzheimer's disease classification M Böhle, F Eitel, M Weygandt, K Ritter Frontiers in aging neuroscience 11, 194, 2019 | 213 | 2019 |
| The role of neural impulse control mechanisms for dietary success in obesity M Weygandt, K Mai, E Dommes, V Leupelt, K Hackmack, T Kahnt, ... Neuroimage 83, 669-678, 2013 | 135 | 2013 |
| Uncovering convolutional neural network decisions for diagnosing multiple sclerosis on conventional MRI using layer-wise relevance propagation F Eitel, E Soehler, J Bellmann-Strobl, AU Brandt, K Ruprecht, RM Giess, ... NeuroImage: Clinical 24, 102003, 2019 | 129 | 2019 |
| Impulse control in the dorsolateral prefrontal cortex counteracts post-diet weight regain in obesity M Weygandt, K Mai, E Dommes, K Ritter, V Leupelt, J Spranger, ... Neuroimage 109, 318-327, 2015 | 109 | 2015 |
| Visualizing convolutional networks for MRI-based diagnosis of Alzheimer’s disease J Rieke, F Eitel, M Weygandt, JD Haynes, K Ritter Understanding and Interpreting Machine Learning in Medical Image Computing …, 2018 | 97 | 2018 |
| Multimodal prediction of conversion to Alzheimer's disease based on incomplete biomarkers K Ritter, J Schumacher, M Weygandt, R Buchert, C Allefeld, JD Haynes, ... Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring 1 (2 …, 2015 | 85 | 2015 |
| Multi-scale classification of disease using structural MRI and wavelet transform K Hackmack, F Paul, M Weygandt, C Allefeld, JD Haynes, ... Neuroimage 62 (1), 48-58, 2012 | 82 | 2012 |
| Testing the robustness of attribution methods for convolutional neural networks in MRI-based Alzheimer’s disease classification F Eitel, K Ritter, Alzheimer’s Disease Neuroimaging Initiative (ADNI) Interpretability of Machine Intelligence in Medical Image Computing and …, 2019 | 69 | 2019 |
| Can we overcome the ‘clinico-radiological paradox’in multiple sclerosis? K Hackmack, M Weygandt, J Wuerfel, CF Pfueller, J Bellmann-Strobl, ... Journal of neurology 259, 2151-2160, 2012 | 66 | 2012 |
| fMRI pattern recognition in obsessive–compulsive disorder M Weygandt, CR Blecker, A Schäfer, K Hackmack, JD Haynes, D Vaitl, ... Neuroimage 60 (2), 1186-1193, 2012 | 58 | 2012 |
| MRI pattern recognition in multiple sclerosis normal-appearing brain areas M Weygandt, K Hackmack, C Pfüller, J Bellmann–Strobl, F Paul, F Zipp, ... PloS one 6 (6), e21138, 2011 | 56 | 2011 |
| Insulin action in the brain regulates mitochondrial stress responses and reduces diet-induced weight gain K Wardelmann, S Blümel, M Rath, E Alfine, C Chudoba, M Schell, W Cai, ... Molecular metabolism 21, 68-81, 2019 | 50 | 2019 |
| Stress-induced brain activity, brain atrophy, and clinical disability in multiple sclerosis M Weygandt, L Meyer-Arndt, JR Behrens, K Wakonig, J Bellmann-Strobl, ... Proceedings of the National Academy of Sciences 113 (47), 13444-13449, 2016 | 33 | 2016 |
| Promises and pitfalls of deep neural networks in neuroimaging-based psychiatric research F Eitel, MA Schulz, M Seiler, H Walter, K Ritter Experimental Neurology 339, 113608, 2021 | 24 | 2021 |
| Performance reserves in brain-imaging-based phenotype prediction MA Schulz, D Bzdok, S Haufe, JD Haynes, K Ritter BioRxiv, 2022.02. 23.481601, 2022 | 19 | 2022 |
| COVID-19: a simple statistical model for predicting intensive care unit load in exponential phases of the disease M Ritter, DVM Ott, F Paul, JD Haynes, K Ritter Scientific Reports 11 (1), 5018, 2021 | 18 | 2021 |
| Generating 3D TOF-MRA volumes and segmentation labels using generative adversarial networks P Subramaniam, T Kossen, K Ritter, A Hennemuth, K Hildebrand, ... Medical Image Analysis 78, 102396, 2022 | 17 | 2022 |
| Structural differences in adolescent brains can predict alcohol misuse RP Rane, EF de Man, JH Kim, K Görgen, M Tschorn, MA Rapp, ... Elife 11, e77545, 2022 | 11 | 2022 |
| The collaborative research center FONDA U Leser, M Hilbrich, C Draxl, P Eisert, L Grunske, P Hostert, D Kainmüller, ... Datenbank-Spektrum 21, 255-260, 2021 | 11 | 2021 |
| Mental speed is associated with the shape irregularity of white matter MRI hyperintensity load C Lange, P Suppa, A Mäurer, K Ritter, U Pietrzyk, E Steinhagen-Thiessen, ... Brain imaging and behavior 11, 1720-1730, 2017 | 11 | 2017 |
