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Reproducibility and Performance of Deep Learning Applications for Cancer Detection in Pathological Images.

, , , , , and . CCGRID, page 621-630. IEEE, (2019)

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Information efficient learning of complexly structured preferences: Elicitation procedures and their application to decision making under uncertainty., , , and . Int. J. Approx. Reason., (2022)A probabilistic evaluation framework for preference aggregation reflecting group homogeneity., , and . Math. Soc. Sci., (2018)The vendor-agnostic EMPAIA platform for integrating AI applications into digital pathology infrastructures., , , , , , , , , and 1 other author(s). Future Gener. Comput. Syst., (2023)Statistical Comparisons of Classifiers by Generalized Stochastic Dominance., , , and . CoRR, (2022)Joining Forces for Pathology Diagnostics with AI Assistance: The EMPAIA Initiative., , , , , , , , , and 10 other author(s). CoRR, (2024)Statistical Models for Partial Orders Based on Data Depth and Formal Concept Analysis., , and . IPMU (2), volume 1602 of Communications in Computer and Information Science, page 17-30. Springer, (2022)In all likelihoods: robust selection of pseudo-labeled data., , , and . ISIPTA, volume 215 of Proceedings of Machine Learning Research, page 412-425. PMLR, (2023)Decision Theory Meets Linear Optimization Beyond Computation., , and . ECSQARU, volume 10369 of Lecture Notes in Computer Science, page 329-339. Springer, (2017)Reproducibility and Performance of Deep Learning Applications for Cancer Detection in Pathological Images., , , , , and . CCGRID, page 621-630. IEEE, (2019)The Minimal Degrees of Faithful Representations of the Sporadic Simple Groups and their Covering Groups.. LMS J. Comput. Math., (2005)