Skip to Main Content (Press Enter)

Logo UNIPV
  • ×
  • Home
  • Degrees
  • Courses
  • Jobs
  • People
  • Outputs
  • Organizations

UNIFIND
Logo UNIPV

|

UNIFIND

unipv.it
  • ×
  • Home
  • Degrees
  • Courses
  • Jobs
  • People
  • Outputs
  • Organizations
  1. Outputs

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

Chapter
Publication Date:
2017
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. © Springer International Publishing AG 2017.
Iris type:
2.1 Contributo in volume (Capitolo o Saggio)
List of contributors:
Gatta, Roberto; Lenkowicz, Jacopo; Vallati, Mauro; Rojas, Eric; Damiani, Andrea; Sacchi, Lucia; De Bari, Berardino; Dagliati, Arianna; Fernandez-Llatas, Carlos; Montesi, Matteo; Marchetti, Antonio; Castellano, Maurizio; Valentini, Vincenzo
Authors of the University:
DAGLIATI ARIANNA
SACCHI LUCIA
Handle:
https://iris.unipv.it/handle/11571/1234347
Book title:
AIME 2017: Artificial Intelligence in Medicine
Published in:
LECTURE NOTES IN COMPUTER SCIENCE
Journal
LECTURE NOTES IN COMPUTER SCIENCE
Series
  • Overview

Overview

URL

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85021642333&doi=10.1007/978-3-319-59758-4_42&partnerID=40&md5=19f7084aa479b231ff23bc81a329aeb9
  • Use of cookies

Powered by VIVO | Designed by Cineca | 26.9.0.0