An early warning system that combines machine learning and a rule-based approach for the prediction of cancer patients’ unplanned visits

dc.contributor.authorWitschel, Hans Friedrich
dc.contributor.authorLaurenzi, Emanuele
dc.contributor.authorJüngling, Stephan
dc.contributor.authorKadvany, Yannick
dc.contributor.authorTrojan, Andreas
dc.contributor.editorMartin, Andreas
dc.contributor.editorFill, Hans-Georg
dc.contributor.editorGerber, Aurona
dc.contributor.editorHinkelmann, Knut
dc.contributor.editorLenat, Doug
dc.contributor.editorStolle, Reinhard
dc.contributor.editorvan Harmelen, Frank
dc.date.accessioned2025-02-21T13:32:38Z
dc.date.issued2023
dc.description.abstract
dc.description.urihttps://nbn-resolving.org/urn:nbn:de:0074-3433-0
dc.eventAAAI 2023 Spring Symposium on Challenges Requiring the Combination of Machine Learning and Knowledge Engineering
dc.event.end2024-03-29
dc.event.start2024-03-27
dc.identifier.doi
dc.identifier.urihttps://irf.fhnw.ch/handle/11654/48276
dc.language.isoen
dc.publisherSun SITE Central Europe
dc.relation.ispartofProceedings of the AAAI 2023 Spring Symposium on Challenges Requiring the Combination of Machine Learning and Knowledge Engineering (AAAI-MAKE 2023)
dc.relation.ispartofseriesCEUR Workshop Proceedings
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.spatialAachen
dc.subject.ddc330 - Wirtschaft
dc.titleAn early warning system that combines machine learning and a rule-based approach for the prediction of cancer patients’ unplanned visits
dc.type04B - Beitrag Konferenzschrift
dspace.entity.typePublication
fhnw.InventedHereYes
fhnw.ReviewTypeAnonymous ex ante peer review of a complete publication
fhnw.affiliation.hochschuleHochschule für Wirtschaftde_CH
fhnw.affiliation.institutInstitut für Wirtschaftsinformatikde_CH
fhnw.openAccessCategoryDiamond
fhnw.publicationStatePublished
fhnw.seriesNumber3433
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relation.isAuthorOfPublication4a2b6cad-6ed6-4355-a377-e408a177b079
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