| Opening the black box of artificial intelligence for clinical decision support: A study predicting stroke outcome E Zihni, VI Madai, M Livne, I Galinovic, AA Khalil, JB Fiebach, D Frey Plos one 15 (4), e0231166, 2020 | 141 | 2020 |
| Outcome prediction in aneurysmal subarachnoid hemorrhage: a comparison of machine learning methods and established clinico-radiological scores NF Dengler, VI Madai, M Unteroberdörster, E Zihni, SC Brune, A Hilbert, ... Neurosurgical Review, 1-10, 2021 | 32 | 2021 |
| Comparing poor and favorable outcome prediction with machine learning after mechanical thrombectomy in acute ischemic stroke MA Mutke, VI Madai, A Hilbert, E Zihni, A Potreck, CS Weyland, ... Frontiers in neurology 13, 737667, 2022 | 13 | 2022 |
| Multimodal fusion strategies for outcome prediction in Stroke E Zihni, JD Kelleher, VI Madai, A Khalil, I Galinovic, J Fiebach, M Livne, ... Technological University Dublin, 2020 | 12 | 2020 |
| Moving toward explainable decisions of artificial intelligence models for the prediction of functional outcomes of ischemic stroke patients E Zihni, B McGarry, J Kelleher Exon Publications, 73-90, 2022 | 3 | 2022 |
| An analysis of the interpretability of neural networks trained on magnetic resonance imaging for stroke outcome prediction E Zihni, BL McGarry, JD Kelleher Proc. Intl. Soc. Mag. Reson. Med 29, 3503, 2021 | 3 | 2021 |
| Enhancing the prediction for shunt-dependent hydrocephalus after aneurysmal subarachnoid hemorrhage using a machine learning approach D Frey, A Hilbert, A Früh, VI Madai, T Kossen, J Kiewitz, J Sommerfeld, ... Neurosurgical Review 46 (1), 206, 2023 | 2 | 2023 |
| A pilot study on the application of explainable deep learning to ADC maps for predicting functional outcome of ischemic stroke patients E Zihni, BL McGarry, J Guo, RG Sah, G Tadros, PA Barber, JD Kelleher | | |
