| Leveraging uncertainty information from deep neural networks for disease detection C Leibig, V Allken, MS Ayhan, P Berens, S Wahl Scientific Reports 7, 2017 | 340 | 2017 |
| Natural Image Bases to Represent Neuroimaging Data A Gupta, MS Ayhan, AS Maida The 30th International Conference on Machine Learning (ICML 2013), 2013 | 232 | 2013 |
| Test-time Data Augmentation for Estimation of Heteroscedastic Aleatoric Uncertainty in Deep Neural Networks MS Ayhan, P Berens International conference on Medical Imaging with Deep Learning (MIDL) 2018, 2018 | 89 | 2018 |
| 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 64, 101724, 2020 | 29 | 2020 |
| 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 | 6 | 2013 |
| Proprietary data formats block health research P Berens, MS Ayhan Nature 565 (7740), 429-429, 2019 | 5 | 2019 |
| Composite kernels for automatic relevance determination in computerized diagnosis of Alzheimer’s disease MS Ayhan, RG Benton, VV Raghavan, S Choubey International Conference on Brain and Health Informatics, 126-137, 2013 | 5 | 2013 |
| 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 |
| 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 77, 102364, 2022 | 3 | 2022 |
| Interpretable gender classification from retinal fundus images using BagNets I Ilanchezian, D Kobak, H Faber, F Ziemssen, P Berens, MS Ayhan International Conference on Medical Image Computing and Computer-Assisted …, 2021 | 3 | 2021 |
| Towards Indefinite Gaussian Processes MS Ayhan, CHH Chu NIPS 2012 Modern Nonparametric Methods in Machine Learning Workshop, 2012 | 3 | 2012 |
| Potential of methods of artificial intelligence for quality assurance P Berens, SM Waldstein, MS Ayhan, L Kuemmerle, H Agostini, A Stahl, ... Der Ophthalmologe: Zeitschrift der Deutschen Ophthalmologischen Gesellschaft …, 2020 | 2* | 2020 |
| 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 | 2 | 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 |
| Multi-task learning for activity detection in neovascular age-related macular degeneration MS Ayhan, H Faber, L Kuehlewein, W Inhoffen, G Aliyeva, F Ziemssen, ... medRxiv, 2022 | | 2022 |
| Efficient and Automatic Subspace Relevance Determination via Multiple Kernel Learning for High-Dimensional Neuroimaging Data MS Ayhan, V Raghavan International Conference on Brain Informatics, 226-238, 2018 | | 2018 |
| A Probabilistic Biomarker for Alzheimer's Disease MS Ayhan University of Louisiana at Lafayette, 2015 | | 2015 |
| Determining Relevant Features based on 3D-SSP to Detect Dementia Caused by Alzheimer's Disease MS Ayhan, RG Benton, VV Raghavan, S Choubey Biotechnology and Bioinformatics Symposium (BIOT-2010), 2010 | | 2010 |
Philipp BerensInstitute for Ophthalmic Research, University of TübingenVerified email at uni-tuebingen.de
