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Best of Both Worlds: Combining Predictive Power with Interpretable and Explainable Results for Patient Pathway Prediction., , , , and . ECIS, (2023)Bringing Light Into the Darkness - A Systematic Literature Review on Explainable Predictive Business Process Monitoring Techniques., , , , , and . ECIS, (2021)Time Matters: Time-Aware LSTMs for Predictive Business Process Monitoring., , , , , and . ICPM Workshops, volume 406 of Lecture Notes in Business Information Processing, page 112-123. Springer, (2020)Predicting Customer Satisfaction in Service Processes Using Multilingual Large Language Models., , , , and . HICSS, page 1488-1497. ScholarSpace, (2024)A Next Click Recommender System for Web-based Service Analytics with Context-aware LSTMs., , , and . HICSS, page 1-10. ScholarSpace, (2020)A technique for determining relevance scores of process activities using graph-based neural networks., , , and . Decis. Support Syst., (2021)GAM(e) changer or not? An evaluation of interpretable machine learning models based on additive model constraints., , , , and . CoRR, (2022)Predictive Business Process Deviation Monitoring., , , , and . ECIS, (2021)Predictive Recommining: Learning Relations Between Event Log Characteristics and Machine Learning Approaches for Supporting Predictive Process Monitoring., , , and . CAiSE Forum, volume 477 of Lecture Notes in Business Information Processing, page 69-76. Springer, (2023)XNAP: Making LSTM-Based Next Activity Predictions Explainable by Using LRP., , , , , and . Business Process Management Workshops, volume 397 of Lecture Notes in Business Information Processing, page 129-141. Springer, (2020)