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http://hdl.handle.net/1942/43676
Title: | From Script to Application. A bupaR Integration into PMApp for Interactive Process Mining Research | Authors: | Tornero-Costa, Roberto Fernandez-Llatas, Carlos MARTIN, Niels JANSSENSWILLEN, Gert VAN HULZEN, Gerard |
Editors: | Juarez, JM Fernandez-Llatas, C Johnson, O Kocbek, P Larranaga, P MARTIN, Niels Munoz-Gama, J Stiglic, G Sepulveda, M Vellido, A |
Issue Date: | 2024 | Publisher: | SPRINGER INTERNATIONAL PUBLISHING AG | Source: | Juarez, JM; Fernandez-Llatas, C; Bielza, C; Johnson, O; Kocbek, P; Larranaga, P; Martin, N; Munoz-Gama, J; Stiglic, G; Sepulveda, M; Vellido, A (Ed.). EXPLAINABLE ARTIFICIAL INTELLIGENCE AND PROCESS MINING APPLICATIONS FOR HEALTHCARE, XAI-HEALTHCARE 2023 & PM4H 2023, SPRINGER INTERNATIONAL PUBLISHING AG, p. 107 -117 | Series/Report: | Communications in Computer and Information Science | Abstract: | There 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. | Notes: | Tornero-Costa, R (corresponding author), Univ Politecn Valencia, Valencia 46022, Spain. rotorcos@itaca.upv.es; carferll@itaca.upv.es; niels.martin@uhasselt.be; gert.janssenswillen@uhasselt.be; gerard.vanhulzen@uhasselt.be |
Keywords: | Interactive Process Mining in Healthcare;Interfaces for Process Oriented Data Science;Process Mining;R;Interactive Process Mining | Document URI: | http://hdl.handle.net/1942/43676 | ISBN: | 978-3-031-54302-9; 978-3-031-54303-6 | DOI: | 10.1007/978-3-031-54303-6_11 | ISI #: | 001265203100011 | Rights: | The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 | Category: | C1 | Type: | Proceedings Paper |
Appears in Collections: | Research publications |
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978-3-031-54303-6.pdf Restricted Access | Published version | 2.57 MB | Adobe PDF | View/Open Request a copy |
ACFrOgATFeuAMvbqH6eRviuhv_Rq2r5O4tPKM9cEWg3-HWYe8bIRvyti6-z8Vy7xtT.pdf Until 2025-02-26 | Peer-reviewed author version | 2.03 MB | Adobe PDF | View/Open Request a copy |
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