Gatta, Roberto, Lenkowicz, Jacopo, Vallati, Mauro, Rojas, Eric, Damiani, Andrea, Sacchi, Lucia, De Bari, Berardino, Dagliati, Anna, Fernandez-Llatas, Carlos, Montesi, Matteo, Marchetti, Antonio, Castellano, Maurizio and Valentini, Vincenzo (2017) pMineR: An Innovative R Library for Performing Process Mining in Medicine. In: Proceedings of the 16th Conference on Artificial Intelligence in Medicine (AIME). Springer, pp. 351-355. ISBN 978-3-319-59758-4
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Abstract
Process Mining is an emerging discipline investigating tasks related with the automated identification of process models, given realworld
data (Process Discovery). The analysis of such models can provide useful insights to domain experts. In addition, models of processes can
be used to test if a given process complies (Conformance Checking) with specifications. For these capabilities, Process Mining is gaining importance and attention in healthcare.
In this paper we introduce pMineR, an R library specifically designed for performing Process Mining in the medical domain, and supporting
human experts by presenting processes in a human-readable way.
Item Type: | Book Chapter |
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Subjects: | Q Science > QA Mathematics > QA76 Computer software R Medicine > R Medicine (General) |
Schools: | School of Computing and Engineering > High-Performance Intelligent Computing > Planning, Autonomy and Representation of Knowledge School of Computing and Engineering > High-Performance Intelligent Computing > Planning, Autonomy and Representation of Knowledge School of Computing and Engineering |
Related URLs: | |
Depositing User: | Mauro Vallati |
Date Deposited: | 28 Mar 2017 15:28 |
Last Modified: | 28 Aug 2021 16:07 |
URI: | http://eprints.hud.ac.uk/id/eprint/31621 |
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