Generating and Comparing Knowledge Graphs of Medical Processes Using pMineR

Roberto Gatta, Mauro Vallati, Jacopo Lenkowicz, 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 proceedingConference contribution

2 Citations (Scopus)

Abstract

Process mining focuses on extracting knowledge, under the form of models, from data generated and stored in information systems. The analysis of generated models can provide useful insights to domain experts. In addition, models of processes can be used to test if a considered process complies with some given specifications. For these reasons, process mining is gaining significant importance in the healthcare domain, where the complexity and flexibility of processes makes extremely hard to evaluate and assess how patients have been treated.
In this paper we describe how pMineR, an R library designed and developed for performing process mining in the medical domain, is currently exploited in Hospitals for supporting domain experts in the analysis of the extracted knowledge models. In its current release, pMineR can encode extracted processes under the form of directed graphs, which are easy to interpret and understand by experts of the domain. It also provides graphical comparison between different processes, allows to model the adherence to a given clinical guidelines and to estimate performance and the workload of the available resources in healthcare
LanguageEnglish
Title of host publicationProceedings of the Ninth Conference on Knowledge Capture (K-CAP), (Austin, TX, 4-6 December 2017)
PublisherAssociation for Computing Machinery (ACM)
Number of pages4
ISBN (Print)9781450355537
DOIs
Publication statusPublished - 4 Dec 2017
Event9th International Conference on Knowledge Capture - Hilton Garden Inn Convention Center, Austin, United States
Duration: 4 Dec 20176 Dec 2017
Conference number: 9
https://k-cap2017.org/ (Link to Conference Website)

Conference

Conference9th International Conference on Knowledge Capture
Abbreviated titleK-CAP 2017
CountryUnited States
CityAustin
Period4/12/176/12/17
Internet address

Fingerprint

Directed graphs
Information systems
Specifications

Cite this

Gatta, R., Vallati, M., Lenkowicz, J., Rojas, E., Damiani, A., Sacchi, L., ... Valentini, V. (2017). Generating and Comparing Knowledge Graphs of Medical Processes Using pMineR. In Proceedings of the Ninth Conference on Knowledge Capture (K-CAP), (Austin, TX, 4-6 December 2017) [36] Association for Computing Machinery (ACM). https://doi.org/10.1145/3148011.3154464
Gatta, Roberto ; Vallati, Mauro ; Lenkowicz, Jacopo ; Rojas, Eric ; Damiani, Andrea ; Sacchi, Lucia ; De Bari, Berardino ; Dagliati, Arianna ; Fernandez-Llatas, Carlos ; Montesi, Matteo ; Marchetti, Antonio ; Castellano, Maurizio ; Valentini, Vincenzo. / Generating and Comparing Knowledge Graphs of Medical Processes Using pMineR. Proceedings of the Ninth Conference on Knowledge Capture (K-CAP), (Austin, TX, 4-6 December 2017). Association for Computing Machinery (ACM), 2017.
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Gatta, R, Vallati, M, Lenkowicz, J, Rojas, E, Damiani, A, Sacchi, L, De Bari, B, Dagliati, A, Fernandez-Llatas, C, Montesi, M, Marchetti, A, Castellano, M & Valentini, V 2017, Generating and Comparing Knowledge Graphs of Medical Processes Using pMineR. in Proceedings of the Ninth Conference on Knowledge Capture (K-CAP), (Austin, TX, 4-6 December 2017)., 36, Association for Computing Machinery (ACM), 9th International Conference on Knowledge Capture, Austin, United States, 4/12/17. https://doi.org/10.1145/3148011.3154464

Generating and Comparing Knowledge Graphs of Medical Processes Using pMineR. / Gatta, Roberto; Vallati, Mauro; Lenkowicz, Jacopo; Rojas, Eric; Damiani, Andrea; Sacchi, Lucia; De Bari, Berardino; Dagliati, Arianna; Fernandez-Llatas, Carlos; Montesi, Matteo; Marchetti, Antonio; Castellano, Maurizio; Valentini, Vincenzo.

Proceedings of the Ninth Conference on Knowledge Capture (K-CAP), (Austin, TX, 4-6 December 2017). Association for Computing Machinery (ACM), 2017. 36.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AU - Gatta, Roberto

AU - Vallati, Mauro

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AU - Castellano, Maurizio

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AB - Process mining focuses on extracting knowledge, under the form of models, from data generated and stored in information systems. The analysis of generated models can provide useful insights to domain experts. In addition, models of processes can be used to test if a considered process complies with some given specifications. For these reasons, process mining is gaining significant importance in the healthcare domain, where the complexity and flexibility of processes makes extremely hard to evaluate and assess how patients have been treated.In this paper we describe how pMineR, an R library designed and developed for performing process mining in the medical domain, is currently exploited in Hospitals for supporting domain experts in the analysis of the extracted knowledge models. In its current release, pMineR can encode extracted processes under the form of directed graphs, which are easy to interpret and understand by experts of the domain. It also provides graphical comparison between different processes, allows to model the adherence to a given clinical guidelines and to estimate performance and the workload of the available resources in healthcare

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M3 - Conference contribution

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PB - Association for Computing Machinery (ACM)

ER -

Gatta R, Vallati M, Lenkowicz J, Rojas E, Damiani A, Sacchi L et al. Generating and Comparing Knowledge Graphs of Medical Processes Using pMineR. In Proceedings of the Ninth Conference on Knowledge Capture (K-CAP), (Austin, TX, 4-6 December 2017). Association for Computing Machinery (ACM). 2017. 36 https://doi.org/10.1145/3148011.3154464