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Ausgewählte Publikationen aus unterschiedlichen Projekten von CLAIM finden Sie hier. 

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  • García-Rudolph A, García-Molina A, Opisso E, Tormos JM, Madai VI, Frey D, et al. Neuropsychological Assessments of Patients With Acquired Brain Injury: A Cluster Analysis Approach to Address Heterogeneity in Web-Based Cognitive Rehabilitation. Front Neurol. 2021;12:1288. Available from:
  • Aydin OU, Taha AA, Hilbert A, Khalil AA, Galinovic I, Fiebach JB, et al. An evaluation of performance measures for arterial brain vessel segmentation. BMC Med Imaging. 2021 Jul 16;21(1):113. Available from:
  • Zicari RV, Ahmed S, Amann J, Braun SA, Brodersen J, Bruneault F, et al. Co-Design of a Trustworthy AI System in Healthcare: Deep Learning Based Skin Lesion Classifier. Front Hum Dyn. 2021;3:40. Available from:
  • Zicari RV, Brusseau J, Blomberg SN, Christensen HC, Coffee M, Ganapini MB, et al. On Assessing Trustworthy AI in Healthcare. Machine Learning as a Supportive Tool to Recognize Cardiac Arrest in Emergency Calls. Front Hum Dyn. 2021;3:30. Available from:
  • Herrgårdh T, Madai VI, Kelleher JD, Magnusson R, Gustafsson M, Milani L, et al. Hybrid modelling for stroke care: Review and suggestions of new approaches for risk assessment and simulation of scenarios. NeuroImage Clin. 2021 Jan 1;31:102694. Available from:
  • Frey D, Livne M, Leppin H, Akay EM, Aydin OU, Behland J, et al. A precision medicine framework for personalized simulation of hemodynamics in cerebrovascular disease. Biomed Eng OnLine. 2021 May 1;20(1). Available from:
  • Ivantsits M, Goubergrits L, Kuhnigk J-M, Huellebrand M, Brüning J, Kossen T, et al. Cerebral Aneurysm Detection and Analysis Challenge 2020 (CADA). In: Hennemuth A, Goubergrits L, Ivantsits M, Kuhnigk J-M, editors. Cerebral Aneurysm Detection and Analysis. Cham: Springer International Publishing; 2021. p. 3–17. (Lecture Notes in Computer Science). Available from:
  • Kossen T, Subramaniam P, Madai VI, Hennemuth A, Hildebrand K, Hilbert A, et al. Synthesizing anonymized and labeled TOF-MRA patches for brain vessel segmentation using generative adversarial networks. Comput Biol Med. 2021 Apr 1;131:104254. Available from:
  • Aydin OU, Taha AA, Hilbert A, Khalil AA, Galinovic I, Fiebach JB, et al. On the usage of average Hausdorff distance for segmentation performance assessment: hidden error when used for ranking. Eur Radiol Exp. 2021 Jan 21;5(1):4. Available from:
  • Dengler NF, Madai VI, Unteroberdörster M, Zihni E, Brune SC, Hilbert A, et al. Outcome prediction in aneurysmal subarachnoid hemorrhage: a comparison of machine learning methods and established clinico-radiological scores. Neurosurg Rev. 2021 Jan 20; Available from:


  • Amann J, Blasimme A, Vayena E, Frey D, Madai VI, the Precise4Q consortium. Explainability for artificial intelligence in healthcare: a multidisciplinary perspective. BMC Med Inform Decis Mak. 2020 Nov 30;20(1):310. Available from:
  • Zihni E, Madai V, Khalil A, Galinovic I, Fiebach J, Kelleher J, et al. Multimodal Fusion Strategies for Outcome Prediction in Stroke. Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies. 2020; Available from: 
  • Hilbert A, Madai VI, Akay EM, Aydin OU, Behland J, Sobesky J, et al. BRAVE-NET: Fully Automated Arterial Brain Vessel Segmentation In Patients with Cerebrovascular Disease. Front Artif Intell. 2020;3. Available from:
  • Higgins D, Madai VI. From Bit to Bedside: A Practical Framework for Artificial Intelligence Product Development in Healthcare. Adv Intell Syst. 2020;2(10):2000052.Available from:
  • Zihni E, Madai VI, Livne M, Galinovic I, Khalil AA, Fiebach JB, et al. Opening the black box of artificial intelligence for clinical decision support: A study predicting stroke outcome. PLOS ONE. 2020;15(4):e0231166. Available from:


  • Livne M, Rieger J, Aydin OU, Taha AA, Akay EM, Kossen T, et al. A U-Net Deep Learning Framework for High Performance Vessel Segmentation in Patients With Cerebrovascular Disease. Front Neurosci. 2019;13. Available from: