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  • Search: subject:"Outcome prediction"
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Year of publication
Subject
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Outcome prediction 4 Artificial intelligence 3 Business process management 3 Deep learning 3 Forecasting model 3 Künstliche Intelligenz 3 Machine learning 3 Prognoseverfahren 3 Learning 2 Lernen 2 Predictive process monitoring 2 Prozessmanagement 2 Bergbau 1 Clinical decision support 1 Data Mining 1 Data mining 1 Data science 1 Early disease detection 1 Efficient delivery 1 Explainable artificial intelligence 1 Faithfulness 1 Health risk prediction 1 Information technology 1 Interpretability 1 Large-scale informatics 1 Learning organization 1 Learning process 1 Lernende Organisation 1 Lernprozess 1 Mining 1 Optimal treatment design and drug delivery 1 Process mining 1 Process outcome prediction 1 Public health and medical preparedness 1 Semi-supervised learning 1 Systems modeling 1
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Online availability
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Free 5
Type of publication
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Article 4 Other 1
Type of publication (narrower categories)
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Article in journal 3 Aufsatz in Zeitschrift 3 Article 1 Audio- / visual Ressource 1
Language
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English 5
Author
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Kratsch, Wolfgang 2 Röglinger, Maximilian 2 Seyfried, Johannes 2 De Smedt, Johannes 1 Folino, Francesco 1 Folino, Gianluigi 1 Guarascio, Massimo 1 Lee, Eva K. 1 Manderscheid, Jonas 1 Manderscheid, Jonas Hans 1 Pontieri, Luigi 1 Stevens, Alexander 1
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Published in...
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Business & information systems engineering 2 Business & Information Systems Engineering 1 European journal of operational research : EJOR 1
Source
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ECONIS (ZBW) 3 BASE 1 EconStor 1
Showing 1 - 5 of 5
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Explainability in process outcome prediction : guidelines to obtain interpretable and faithful models
Stevens, Alexander; De Smedt, Johannes - In: European journal of operational research : EJOR 317 (2024) 2, pp. 317-329
Persistent link: https://www.econbiz.de/10014635794
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Semi-supervised discovery of DNN-based outcome predictors from scarcely-labeled process logs
Folino, Francesco; Folino, Gianluigi; Guarascio, Massimo; … - In: Business & information systems engineering 64 (2022) 6, pp. 729-749
Persistent link: https://www.econbiz.de/10013483362
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Machine learning in business process monitoring : a comparison of deep learning and classical approaches used for outcome prediction
Kratsch, Wolfgang; Manderscheid, Jonas Hans; … - In: Business & information systems engineering 63 (2021) 3, pp. 261-276
Persistent link: https://www.econbiz.de/10012542845
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Machine Learning in Business Process Monitoring: A Comparison of Deep Learning and Classical Approaches Used for Outcome Prediction
Kratsch, Wolfgang; Manderscheid, Jonas; Röglinger, … - In: Business & Information Systems Engineering 63 (2020) 3, pp. 261-276
Predictive process monitoring aims at forecasting the behavior, performance, and outcomes of business processes at runtime. It helps identify problems before they occur and re-allocate resources before they are wasted. Although deep learning (DL) has yielded breakthroughs, most existing...
Persistent link: https://www.econbiz.de/10014503822
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Modeling and Informatics Advances in Medicine and HealthCare -- basic research, clinical decision making, and efficient delivery
Lee, Eva K. - 2009
treatment design, and outcome prediction. For health risk prediction and early disease diagnosis, three applications are …
Persistent link: https://www.econbiz.de/10009475807
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