Expertise

  • Computer Science

    • User
    • Models
    • Domains
    • Records
    • Accuracy
    • Visualization
    • Machine Learning
    • Evaluation

Organisations

Publications

2024
Prototype-based Interpretable Breast Cancer Prediction Models: Analysis and Challenges. Pathak, S., Schlötterer, J., Veltman, J., Geerdink, J., Keulen, M. v. & Seifert, C.Interpreting and Correcting Medical Image Classification with PIP-NetIn Artificial Intelligence. ECAI 2023 International Workshops - XAI^3, TACTIFUL, XI-ML, SEDAMI, RAAIT, AI4S, HYDRA, AI4AI, 2023, Proceedings (pp. 198-215). Springer. Nauta, M., Hegeman, J. H., Geerdink, J., Schlötterer, J., Keulen, M. v. & Seifert, C.https://doi.org/10.1007/978-3-031-50396-2_11
2023
From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AIACM computing surveys, 55(13s), Article 295. Nauta, M., Trienes, J., Pathak, S., Nguyen, E., Peters, M., Schmitt, Y., Schlötterer, J., Van Keulen, M. & Seifert, C.https://doi.org/10.1145/3583558Weakly Supervised Learning for Breast Cancer Prediction on Mammograms in Realistic Settings. ArXiv.org. Pathak, S., Schlötterer, J., Geerdink, J., Vijlbrief, O. D., Keulen, M. v. & Seifert, C.Benchmarking eXplainable AI: A Survey on Available Toolkits and Open ChallengesIn Proceedings of the 32nd International Joint Conference on Artificial Intelligence, IJCAI 2023 (pp. 6665-6673). International Joint Conferences on Artificial Intelligence. Le, P. Q., Nauta, M., Nguyen, V. B., Pathak, S., Schlötterer, J. & Seifert, C.Interpreting and Correcting Medical Image Classification with PIP-Net. ArXiv.org. Nauta, M., Hegeman, J. H., Geerdink, J., Schlötterer, J., Keulen, M. v. & Seifert, C.https://doi.org/10.48550/arXiv.2307.10404Know What Not To Know: Users’ Perception of Abstaining ClassifiersIn Companion Publication of the 2023 ACM Designing Interactive Systems Conference (pp. 169-172). Association for Computing Machinery. Papenmeier, A., Hienert, D., Kammerer, Y., Seifert, C. & Kern, D.https://doi.org/10.1145/3563703.3596622PIP-Net: Patch-Based Intuitive Prototypes for Interpretable Image ClassificationIn CVPR 2023 (pp. 2744-2753). Nauta, M., Schlötterer, J., van Keulen, M. & Seifert, C.PIP-Net: Patch-Based Intuitive Prototypes for Interpretable Image Classification. Nauta, M., Schlötterer, J., van Keulen, M. & Seifert, C.Explainable AI in medical imaging: An overview for clinical practitioners – Beyond saliency-based XAI approachesEuropean journal of radiology, 162, Article 110786. Borys, K., Schmitt, Y. A., Nauta, M., Seifert, C., Krämer, N., Friedrich, C. M. & Nensa, F.https://doi.org/10.1016/j.ejrad.2023.110786

Research profiles

Courses academic year 2023/2024

Courses in the current academic year are added at the moment they are finalised in the Osiris system. Therefore it is possible that the list is not yet complete for the whole academic year.

Courses academic year 2022/2023

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University of Twente

Zilverling (building no. 11)
Hallenweg 19
7522 NH Enschede
Netherlands

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