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  • Search: subject:"Process prediction"
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Year of publication
Subject
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Process prediction 5 Deep learning 3 Forecasting model 3 Prognoseverfahren 3 Artificial intelligence 2 Generalization 2 Interpretability 2 Interpretable machine learning 2 Interpretation plots 2 Künstliche Intelligenz 2 Next activity prediction 2 Patient pathway 2 Predictive process monitoring 2 Sepsis 2 Validity issues 2 Algorithm 1 Algorithmus 1 Business process management 1 Feature hashing 1 Forecast 1 Hospital 1 Krankenhaus 1 N-grams 1 Patienten 1 Patients 1 Prognose 1 Prozessmanagement 1 Stacked autoencoders 1
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Online availability
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Free 4 Undetermined 1
Type of publication
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Article 5
Type of publication (narrower categories)
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Article in journal 3 Aufsatz in Zeitschrift 3 Article 2
Language
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English 5
Author
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Fettke, Peter 3 Abb, Luka 2 Kraus, Mathias 2 Matzner, Martin 2 Pfeiffer, Peter 2 Rehse, Jana-Rebecca 2 Weinzierl, Sven 2 Zilker, Sandra 2 Zschech, Patrick 2 Evermann, Joerg 1 Mehdiyev, Nijat 1
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Published in...
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Business & information systems engineering 2 Business & Information Systems Engineering 1 Health Care Management Science 1 Health care management science : a new journal serving the international health care management community 1
Source
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ECONIS (ZBW) 3 EconStor 2
Showing 1 - 5 of 5
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Learning from the data to predict the process : generalization capabilities of next activity prediction algorithms
Pfeiffer, Peter; Abb, Luka; Fettke, Peter; Rehse, … - In: Business & information systems engineering 67 (2025) 3, pp. 357-383
Persistent link: https://www.econbiz.de/10015470801
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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
Zilker, Sandra; Weinzierl, Sven; Kraus, Mathias; … - In: Health care management science : a new journal serving … 27 (2024) 2, pp. 136-167
Persistent link: https://www.econbiz.de/10015079848
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Cover Image
Learning from the Data to Predict the Process
Pfeiffer, Peter; Abb, Luka; Fettke, Peter; Rehse, … - In: Business & Information Systems Engineering 67 (2025) 3, pp. 357-383
Predictive process monitoring (PPM) aims to forecast how a running process instance will unfold in the future, e.g., which activity will be executed next. For this purpose, PPM techniques rely on machine learning models trained on historical event log data. Such models are assumed to learn an...
Persistent link: https://www.econbiz.de/10015506605
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A novel business process prediction model using a deep learning method
Mehdiyev, Nijat; Evermann, Joerg; Fettke, Peter - In: Business & information systems engineering 62 (2020) 2, pp. 143-157
Persistent link: https://www.econbiz.de/10012242462
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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
Zilker, Sandra; Weinzierl, Sven; Kraus, Mathias; … - In: Health Care Management Science 27 (2024) 2, pp. 136-167
Proactive analysis of patient pathways helps healthcare providers anticipate treatment-related risks, identify outcomes, and allocate resources. Machine learning (ML) can leverage a patient’s complete health history to make informed decisions about future events. However, previous work has...
Persistent link: https://www.econbiz.de/10015361777
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