Sandra Zilker

Lehrstuhl für Digital Industrial Service Systems

Machine learning in business process management: A systematic literature review (2024) Weinzierl S, Zilker S, Dunzer S, Matzner M Journal article, Review article A machine learning framework for interpretable predictions in patient pathways: The case of predicting ICU admission for patients with symptoms of sepsis (2024) Zilker S, Weinzierl S, Kraus M, Zschech P, Matzner M Journal article, Original article Transfer learning for predictive process monitoring (2024) Ließmann A, Wang W, Weinzierl S, Zilker S, Matzner M Conference contribution, Conference Contribution Towards automated business process redesign in runtime using generative machine learning (2024) Harl M, Zilker S, Weinzierl S Conference contribution, Conference Contribution Predicting customer satisfaction in service processes using multilingual large language models (2024) Ließmann A, Zilker S, Weinzierl S, Sukhareva M, Matzner M Conference contribution, Conference Contribution Context-aware explanations of accurate predictions in service processes (2024) Weinzierl S, Zilker S, Brunk J, Revoredo K, Matzner M, Becker J Conference contribution, Conference Contribution Design Principles for Using Business Process Management Systems (2023) Dunzer S, Tang W, Höchstädter N, Zilker S, Matzner M Book chapter / Article in edited volumes Design Principles for Using Business Process Management Systems (2023) Dunzer S, Tang W, Höchstädter N, Zilker S, Matzner M Conference contribution, Conference Contribution Best of both worlds: Combining predictive power with interpretable and explainable results for patient pathway prediction (2023) Zilker S, Weinzierl S, Zschech P, Kraus M, Matzner M Conference contribution, Conference Contribution A method for predicting workarounds in business processes (2022) Weinzierl S, Bartelheimer C, Zilker S, Beverungen D, Matzner M Conference contribution, Conference Contribution