Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/42588
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dc.contributor.authorTornero-Costa, Roberto-
dc.contributor.authorFernandez-Llatas, Carlos-
dc.contributor.authorMARTIN, Niels-
dc.contributor.authorJANSSENSWILLEN, Gert-
dc.contributor.authorVAN HULZEN, Gerard-
dc.date.accessioned2024-03-11T16:26:06Z-
dc.date.available2024-03-11T16:26:06Z-
dc.date.issued2024-
dc.date.submitted2024-02-29T10:35:00Z-
dc.identifier.citationJuarez, Jose M.; Fernandez-Llatas, Carlos; Bielza, Concha; Johnson, Owen; Kocbek, Primoz; Larrañaga, Pedro; Martin, Niels; Munoz-Gama, Jorge; Štiglic, Gregor; Sepulveda, Marcos; Vellido, Alfredo (Ed.). Explainable Artificial Intelligence and Process Mining Applications for Healthcare Third International Workshop, XAI-Healthcare 2023, and First International Workshop, PM4H 2023, Portoroz, Slovenia, June 15, 2023, Proceedings, Springer, p. 107 -117-
dc.identifier.isbn9783031543029-
dc.identifier.isbn9783031543036-
dc.identifier.issn1865-0929-
dc.identifier.issn1865-0937-
dc.identifier.urihttp://hdl.handle.net/1942/42588-
dc.description.abstractThere are several open-source Process Mining tools available for research purposes. PMApp is an Interactive Process Mining toolkit developed to facilitate process discovery and analysis in healthcare. PMApp is designed to introduce healthcare professionals to Process Mining, simplifying the learning process by reducing the need for extensive coding knowledge. With PMApp, users can easily apply process mining techniques to healthcare data without the steep learning curve typically associated with coding languages. At the same time, bupaR is an open-source, integrated suite of R-packages for handling and analysing process data. bupaR provides support for different stages in process analysis and offers the flexibility of coding tools. Given the complementarity between both tools, this paper outlines how PMApp has been extended to integrate R code and bupaR functionalities. This integration provides an opportunity to extend research in process mining by combining two powerful tools. The paper will showcase the feasibility of this integration and demonstrate how researchers and clinicians can leverage the combined capabilities of Interactive Process Mining and scripting open-source tools to gain insights into complex healthcare processes.-
dc.language.isoen-
dc.publisherSpringer-
dc.relation.ispartofseriesCommunications in Computer and Information Science-
dc.subject.otherInteractive Process Mining in Healthcare-
dc.subject.otherInterfaces for Process Oriented Data Science-
dc.subject.otherProcess Mining-
dc.subject.otherR-
dc.subject.otherInteractive Process Mining-
dc.titleFrom Script to Application. A bupaR Integration into PMApp for Interactive Process Mining Research-
dc.typeProceedings Paper-
local.bibliographicCitation.authorsJuarez, Jose M.-
local.bibliographicCitation.authorsFernandez-Llatas, Carlos-
local.bibliographicCitation.authorsBielza, Concha-
local.bibliographicCitation.authorsJohnson, Owen-
local.bibliographicCitation.authorsKocbek, Primoz-
local.bibliographicCitation.authorsLarrañaga, Pedro-
local.bibliographicCitation.authorsMartin, Niels-
local.bibliographicCitation.authorsMunoz-Gama, Jorge-
local.bibliographicCitation.authorsŠtiglic, Gregor-
local.bibliographicCitation.authorsSepulveda, Marcos-
local.bibliographicCitation.authorsVellido, Alfredo-
local.bibliographicCitation.conferencedateJune 15, 2023-
local.bibliographicCitation.conferencenameThird International Workshop, XAI-Healthcare 2023, and First International Workshop, PM4H 2023-
local.bibliographicCitation.conferenceplacePortoroz, Slovenia-
dc.identifier.epage117-
dc.identifier.spage107-
dc.identifier.volume2020-
local.bibliographicCitation.jcatC1-
local.type.refereedRefereed-
local.type.specifiedProceedings Paper-
local.relation.ispartofseriesnr2020-
local.bibliographicCitation.statusEarly view-
dc.identifier.doi10.1007/978-3-031-54303-6_11-
local.provider.typeCrossRef-
local.bibliographicCitation.btitleExplainable Artificial Intelligence and Process Mining Applications for Healthcare Third International Workshop, XAI-Healthcare 2023, and First International Workshop, PM4H 2023, Portoroz, Slovenia, June 15, 2023, Proceedings-
local.uhasselt.internationalyes-
item.embargoEndDate2025-03-11-
item.fullcitationTornero-Costa, Roberto; Fernandez-Llatas, Carlos; MARTIN, Niels; JANSSENSWILLEN, Gert & VAN HULZEN, Gerard (2024) From Script to Application. A bupaR Integration into PMApp for Interactive Process Mining Research. In: Juarez, Jose M.; Fernandez-Llatas, Carlos; Bielza, Concha; Johnson, Owen; Kocbek, Primoz; Larrañaga, Pedro; Martin, Niels; Munoz-Gama, Jorge; Štiglic, Gregor; Sepulveda, Marcos; Vellido, Alfredo (Ed.). Explainable Artificial Intelligence and Process Mining Applications for Healthcare Third International Workshop, XAI-Healthcare 2023, and First International Workshop, PM4H 2023, Portoroz, Slovenia, June 15, 2023, Proceedings, Springer, p. 107 -117.-
item.contributorTornero-Costa, Roberto-
item.contributorFernandez-Llatas, Carlos-
item.contributorMARTIN, Niels-
item.contributorJANSSENSWILLEN, Gert-
item.contributorVAN HULZEN, Gerard-
item.accessRightsEmbargoed Access-
item.fulltextWith Fulltext-
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