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Kerstin Ritter geb. Hackmack
Kerstin Ritter geb. Hackmack
Bernstein Center for Computational Neuroscience, Charité-Universitätsmedizin Berlin
Bestätigte E-Mail-Adresse bei bccn-berlin.de - Startseite
Titel
Zitiert von
Zitiert von
Jahr
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
2502019
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
1572019
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
1432013
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
1142015
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
1062018
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
892015
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
872012
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
772019
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
672012
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
602011
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
582019
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
582012
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
372016
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
332021
Performance reserves in brain-imaging-based phenotype prediction
MA Schulz, D Bzdok, S Haufe, JD Haynes, K Ritter
Cell Reports 43 (1), 2024
292024
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
262022
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
212021
Deep neural network heatmaps capture Alzheimer’s disease patterns reported in a large meta-analysis of neuroimaging studies
D Wang, N Honnorat, PT Fox, K Ritter, SB Eickhoff, S Seshadri, M Habes, ...
Neuroimage 269, 119929, 2023
202023
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
132021
MRI-based diagnostic biomarkers for early onset pediatric multiple sclerosis
M Weygandt, HM Hummel, K Schregel, K Ritter, C Allefeld, E Dommes, ...
NeuroImage: Clinical 7, 400-408, 2015
132015
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