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On the feasibility of distributed process mining in healthcare

Contributo in Atti di convegno
Data di Pubblicazione:
2019
Abstract:
Process mining is gaining significant importance in the healthcare domain, where the quality of services depends on the suitable and efficient execution of processes. A pivotal challenge for the application of process mining in the healthcare domain comes from the growing importance of multi-centric studies, where privacy-preserving techniques are strongly needed. In this paper, building on top of the well-known Alpha algorithm, we introduce a distributed process mining approach, that allows to overcome problems related to privacy and data being spread around. The introduced technique allows to perform process mining without sharing any patients-related information, thus ensuring privacy and maximizing the possibility of cooperation among hospitals.
Tipologia CRIS:
4.1 Contributo in Atti di convegno
Keywords:
Distributed learning; Healthcare; Process mining
Elenco autori:
Gatta, R.; Vallati, M.; Lenkowicz, J.; Masciocchi, C.; Cellini, F.; Boldrini, L.; Llatas, C. F.; Valentini, V.; Damiani, A.
Autori di Ateneo:
GATTA ROBERTO
Link alla scheda completa:
https://iris.unibs.it/handle/11379/546271
Titolo del libro:
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pubblicato in:
LECTURE NOTES IN ARTIFICIAL INTELLIGENCE
Journal
LECTURE NOTES IN ARTIFICIAL INTELLIGENCE
Series
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