@inproceedings{cbfaacd5771d40368856f5e5243fb710,
title = "pMineR: An innovative R library for performing process mining in medicine",
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.",
keywords = "Decision support system, Process mining, R",
author = "Roberto Gatta and Jacopo Lenkowicz and Mauro Vallati and Eric Rojas and Andrea Damiani and Lucia Sacchi and {De Bari}, Berardino and Arianna Dagliati and Carlos Fernandez-Llatas and Matteo Montesi and Antonio Marchetti and Maurizio Castellano and Vincenzo Valentini",
year = "2017",
month = jan,
day = "1",
doi = "10.1007/978-3-319-59758-4_42",
language = "English",
isbn = "9783319597577",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Nature",
pages = "351--355",
editor = "{[surname]ten Teije}, Annette and Christian Popow and Lucia Sacchi and Holmes, {John H.}",
booktitle = "Artificial Intelligence in Medicine - 16th Conference on Artificial Intelligence in Medicine, AIME 2017, Proceedings",
address = "United States",
note = "16th Conference on Artificial Intelligence in Medicine, AIME 2017 ; Conference date: 21-06-2017 Through 24-06-2017",
}