Machine learning in business process management: A systematic literature review von Weinzierl, Sven, Zilker, Sandra, Dunzer, Sebastian, Matzner, Martin

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A machine learning framework for interpretable predictions in patient pathways: The case of predicting ICU admission for patients with symptoms of sepsis von Zilker, Sandra, Weinzierl, Sven, Kraus, Mathias, Zschech, Patrick, Matzner, Martin

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Prescriptive Business Process Monitoring for Recommending Next Best Actions von Weinzierl, Sven, Dunzer, Sebastian, Zilker, Sandra, Matzner, Martin

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The Evaluation of the Black Box Problem for AI-Based Recommendations: An Interview-Based Study von Ochmann, Jessica, Zilker, Sandra, Laumer, Sven

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Text-Aware Predictive Process Monitoring with Contextualized Word Embeddings von Cabrera, Lena, Weinzierl, Sven, Zilker, Sandra, Matzner, Martin

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XNAP: Making LSTM-Based Next Activity Predictions Explainable by Using LRP von Weinzierl, Sven, Zilker, Sandra, Brunk, Jens, Revoredo, Kate, Matzner, Martin, Becker, Jörg

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Design Principles for Using Business Process Management Systems von Dunzer, Sebastian, Tang, Willi, Höchstädter, Nico, Zilker, Sandra, Matzner, Martin

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The Status Quo of Process Mining in the Industrial Sector von Dunzer, Sebastian, Zilker, Sandra, Marx, Emanuel, Grundler, Valentin, Matzner, Martin

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Machine learning in business process management: A systematic literature review von Weinzierl, Sven, Zilker, Sandra, Dunzer, Sebastian, Matzner, Martin

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A machine learning framework for interpretable predictions in patient pathways: The case of predicting ICU admission for patients with symptoms of sepsis von Zilker, Sandra, Weinzierl, Sven, Kraus, Mathias, Zschech, Patrick, Matzner, Martin

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Challenging the Performance-Interpretability Trade-off: An Evaluation of Interpretable Machine Learning Models von Kruschel, Sven, Hambauer, Nico, Weinzierl, Sven, Zilker, Sandra, Kraus, Mathias, Zschech, Patrick

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GAM(e) changer or not? An evaluation of interpretable machine learning models based on additive model constraints von Zschech, Patrick, Weinzierl, Sven, Hambauer, Nico, Zilker, Sandra, Kraus, Mathias

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Prescriptive Business Process Monitoring for Recommending Next Best Actions von Weinzierl, Sven, Dunzer, Sebastian, Zilker, Sandra, Matzner, Martin

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A machine learning framework for interpretable predictions in patient pathways: The case of predicting ICU admission for patients with symptoms of sepsis von Zilker, Sandra, Weinzierl, Sven, Kraus, Mathias, Zschech, Patrick, Matzner, Martin

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Challenging the Performance-Interpretability Trade-off: An Evaluation of Interpretable Machine Learning Models von Kruschel, Sven, Hambauer, Nico, Weinzierl, Sven, Zilker, Sandra, Kraus, Mathias, Zschech, Patrick

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XNAP: Making LSTM-based Next Activity Predictions Explainable by Using LRP von Weinzierl, Sven, Zilker, Sandra, Brunk, Jens, Revoredo, Kate, Matzner, Martin, Becker, Jörg

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GAM(e) changer or not? An evaluation of interpretable machine learning models based on additive model constraints von Zschech, Patrick, Weinzierl, Sven, Hambauer, Nico, Zilker, Sandra, Kraus, Mathias

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XNAP: Making LSTM-based Next Activity Predictions Explainable by Using LRP von Weinzierl, Sven, Zilker, Sandra, Brunk, Jens, Revoredo, Kate, Matzner, Martin, Becker, Jörg

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