Leveraging uncertainty information from deep neural networks for disease detection C Leibig, V Allken, MS Ayhan, P Berens, S Wahl Scientific Reports, 2017 | 532 | 2017 |
Natural Image Bases to Represent Neuroimaging Data A Gupta, MS Ayhan, AS Maida ICML 2013, 2013 | 298 | 2013 |
Test-time Data Augmentation for Estimation of Heteroscedastic Aleatoric Uncertainty in Deep Neural Networks MS Ayhan, P Berens Medical Imaging with Deep Learning (MIDL) 2018, 2018 | 210 | 2018 |
A foundation model for generalizable disease detection from retinal images Y Zhou, MA Chia, SK Wagner, MS Ayhan, DJ Williamson, RR Struyven, ... Nature, 2023 | 133 | 2023 |
Expert-validated estimation of diagnostic uncertainty for deep neural networks in diabetic retinopathy detection MS Ayhan, L Kühlewein, G Aliyeva, W Inhoffen, F Ziemssen, P Berens Medical Image Analysis, 2020 | 76 | 2020 |
Clinical validation of saliency maps for understanding deep neural networks in ophthalmology MS Ayhan, LB Kümmerle, L Kühlewein, W Inhoffen, G Aliyeva, ... Medical Image Analysis, 2022 | 34 | 2022 |
Interpretable gender classification from retinal fundus images using BagNets I Ilanchezian, D Kobak, H Faber, F Ziemssen, P Berens, MS Ayhan MICCAI 2021, 2021 | 19 | 2021 |
Visual explanations for the detection of diabetic retinopathy from retinal fundus images V Boreiko, I Ilanchezian, MS Ayhan, S Müller, LM Koch, H Faber, ... MICCAI 2022, 2022 | 11 | 2022 |
Proprietary data formats block health research P Berens, MS Ayhan Nature, 2019 | 8 | 2019 |
Exploitation of 3D stereotactic surface projection for predictive modelling of Alzheimer’s disease MS Ayhan, RG Benton, VV Raghavan, S Choubey International Journal of Data Mining and Bioinformatics 7 (2), 146-165, 2013 | 7 | 2013 |
Composite kernels for automatic relevance determination in computerized diagnosis of Alzheimer’s disease MS Ayhan, RG Benton, VV Raghavan, S Choubey Brain and Health Informatics: International Conference, BHI 2013, Maebashi …, 2013 | 5 | 2013 |
Towards Indefinite Gaussian Processes MS Ayhan, CHH Chu NIPS 2012 Modern Nonparametric Methods in Machine Learning Workshop, 2012 | 5 | 2012 |
Potential of methods of artificial intelligence for quality assurance P Berens, SM Waldstein, MS Ayhan, L Kuemmerle, H Agostini, A Stahl, ... Der Ophthalmologe 117, 320-325, 2020 | 4* | 2020 |
Utilization of domain-knowledge for simplicity and comprehensibility in predictive modeling of Alzheimer's disease MS Ayhan, RG Benton, VV Raghavan, S Choubey 2012 IEEE International Conference on Bioinformatics and Biomedicine …, 2012 | 4 | 2012 |
Exploitation of 3D Stereotactic Surface Projection for automated classification of Alzheimer's disease according to dementia levels MS Ayhan, RG Benton, VV Raghavan, S Choubey 2010 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2010 | 4 | 2010 |
Multitask Learning for Activity Detection in Neovascular Age-Related Macular Degeneration MS Ayhan, H Faber, L Kühlewein, W Inhoffen, G Aliyeva, F Ziemssen, ... Translational Vision Science & Technology (TVST), 2023 | 3 | 2023 |
Evaluation of Autoencoders for Bases to Represent Neuroimaging Data A Gupta, MS Ayhan, AS Maida NIPS 2013 Workshop on Machine Learning and Interpretation in NeuroImaging, 2013 | 3 | 2013 |
Multiple kernel learning and automatic subspace relevance determination for high-dimensional neuroimaging data MS Ayhan, V Raghavan arXiv preprint arXiv:1706.00856, 2017 | 1 | 2017 |
Interpretable detection of epiretinal membrane from optical coherence tomography with deep neural networks MS Ayhan, J Neubauer, MM Uzel, F Gelisken, P Berens Scientific Reports, 2024 | | 2024 |
Generating Realistic Counterfactuals for Retinal Fundus and OCT Images using Diffusion Models I Ilanchezian, V Boreiko, L Kühlewein, Z Huang, MS Ayhan, M Hein, ... arXiv preprint arXiv:2311.11629, 2023 | | 2023 |