pMineR: An Innovative R Library for Performing Process Mining in Medicine

Roberto Gatta; Jacopo Lenkowicz[; Mauro Vallati; Eric Rojas; Andrea Damiani; Lucia Sacchi; Berardino De Bari; Arianna Dagliati; Carlos Fernandez-Llatas; Matteo Montesi; Antonio Marchetti; Maurizio Castellano; Vincenzo Valentini

doi:10.1007/978-3-319-59758-4_42

pMineR: An Innovative R Library for Performing Process Mining in Medicine

Roberto Gatta, Jacopo Lenkowicz[, Mauro Vallati, Eric Rojas, Andrea Damiani, Lucia Sacchi, Berardino De Bari, Arianna Dagliati, Carlos Fernandez-Llatas, Matteo Montesi, Antonio Marchetti, Maurizio Castellano, Vincenzo Valentini

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

46 Citations (Scopus)

Abstract

Process Mining is an emerging discipline investigating tasks related with the automated identification of process models, given real world 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.

Original language	English
Title of host publication	Artificial Intelligence in Medicine
Subtitle of host publication	Proceedings of the 16th Conference on Artificial Intelligence in Medicine
Publisher	Springer International Publishing AG
Pages	351-355
Number of pages	5
ISBN (Electronic)	9783319597584
ISBN (Print)	9783319597577
DOIs	https://doi.org/10.1007/978-3-319-59758-4_42
Publication status	Published - Jun 2017
Event	16th Conference on Artificial Intelligence in Medicine - Vienna, Austria Duration: 21 Jun 2017 → 24 Jun 2017 Conference number: 16 http://aime17.aimedicine.info/ (Link to Conference Website )

Publication series

Name	Lecture Notes in Artificial Intelligence
Publisher	Springer International

Conference

Conference	16th Conference on Artificial Intelligence in Medicine
Abbreviated title	AIME 2017
Country/Territory	Austria
City	Vienna
Period	21/06/17 → 24/06/17
Internet address	http://aime17.aimedicine.info/ (Link to Conference Website )

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-319-59758-4_42Licence: Other

http://eprints.hud.ac.uk/id/eprint/31621/Licence: Unspecified

Cite this

Gatta, R., Lenkowicz[, J., Vallati, M., Rojas, E., Damiani, A., Sacchi, L., De Bari, B., Dagliati, A., Fernandez-Llatas, C., Montesi, M., Marchetti, A., Castellano, M., & Valentini, V. (2017). pMineR: An Innovative R Library for Performing Process Mining in Medicine. In Artificial Intelligence in Medicine: Proceedings of the 16th Conference on Artificial Intelligence in Medicine (pp. 351-355). (Lecture Notes in Artificial Intelligence). Springer International Publishing AG. https://doi.org/10.1007/978-3-319-59758-4_42

@inproceedings{78db5a5df53d48258ca3e946e17d587e,

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 real world 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 = "process mining, decision support",

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 = jun,

doi = "10.1007/978-3-319-59758-4_42",

language = "English",

isbn = "9783319597577",

series = "Lecture Notes in Artificial Intelligence",

publisher = "Springer International Publishing AG",

pages = "351--355",

booktitle = "Artificial Intelligence in Medicine",

address = "Switzerland",

note = "16th Conference on Artificial Intelligence in Medicine, AIME 2017 ; Conference date: 21-06-2017 Through 24-06-2017",

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Gatta, R, Lenkowicz[, J, Vallati, M, Rojas, E, Damiani, A, Sacchi, L, De Bari, B, Dagliati, A, Fernandez-Llatas, C, Montesi, M, Marchetti, A, Castellano, M & Valentini, V 2017, pMineR: An Innovative R Library for Performing Process Mining in Medicine. in Artificial Intelligence in Medicine: Proceedings of the 16th Conference on Artificial Intelligence in Medicine. Lecture Notes in Artificial Intelligence, Springer International Publishing AG, pp. 351-355, 16th Conference on Artificial Intelligence in Medicine, Vienna, Austria, 21/06/17. https://doi.org/10.1007/978-3-319-59758-4_42

pMineR : An Innovative R Library for Performing Process Mining in Medicine. / Gatta, Roberto; Lenkowicz[, Jacopo; Vallati, Mauro et al.

Artificial Intelligence in Medicine: Proceedings of the 16th Conference on Artificial Intelligence in Medicine. Springer International Publishing AG, 2017. p. 351-355 (Lecture Notes in Artificial Intelligence).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - pMineR

T2 - 16th Conference on Artificial Intelligence in Medicine

AU - Gatta, Roberto

AU - Lenkowicz[, Jacopo

AU - Vallati, Mauro

AU - Rojas, Eric

AU - Damiani, Andrea

AU - Sacchi, Lucia

AU - De Bari, Berardino

AU - Dagliati, Arianna

AU - Fernandez-Llatas, Carlos

AU - Montesi, Matteo

AU - Marchetti, Antonio

AU - Castellano, Maurizio

AU - Valentini, Vincenzo

N1 - Conference code: 16

PY - 2017/6

Y1 - 2017/6

N2 - Process Mining is an emerging discipline investigating tasks related with the automated identification of process models, given real world 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.

AB - Process Mining is an emerging discipline investigating tasks related with the automated identification of process models, given real world 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.

KW - process mining

KW - decision support

UR - https://link.springer.com/book/10.1007/978-3-319-59758-4#about

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SN - 9783319597577

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SP - 351

EP - 355

BT - Artificial Intelligence in Medicine

PB - Springer International Publishing AG

Y2 - 21 June 2017 through 24 June 2017

ER -

Gatta R, Lenkowicz[ J, Vallati M, Rojas E, Damiani A, Sacchi L et al. pMineR: An Innovative R Library for Performing Process Mining in Medicine. In Artificial Intelligence in Medicine: Proceedings of the 16th Conference on Artificial Intelligence in Medicine. Springer International Publishing AG. 2017. p. 351-355. (Lecture Notes in Artificial Intelligence). Epub 2017 May 30. doi: 10.1007/978-3-319-59758-4_42

pMineR: An Innovative R Library for Performing Process Mining in Medicine

Abstract

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Conference

UN SDGs

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