Ontology Model for Supporting Process Mining on Healthcare-Related Data

被引：1

作者：

Antonio Minarro-Gimenez, Jose ^{[1
]}

Fernandez-Llatas, Carlos ^{[2
]}

Martinez-Salvador, Begona ^{[3
]}

Martinez-Costa, Catalina ^{[1
]}

Marcos, Mar ^{[3
]}

Tomas Fernandez-Breis, Jesualdo ^{[1
]}

机构：

[1] Univ Murcia, Dept Informat & Sistemas, IMIB Arrixaca, CEIR Campus Mare Nostrum, Murcia, Spain

[2] SABIEN ITACA Univ Politecn Valencia, Valencia, Spain

[3] Univ Jaume 1, Dept Comp Engn & Sci, Castellon de La Plana, Spain

来源：

ARTIFICIAL INTELLIGENCE IN MEDICINE, AIME 2023 | 2023年 / 13897卷

关键词：

Clinical Process Ontology; Process Mining; Electronic Health Record;

D O I：

10.1007/978-3-031-34344-5_42

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In the field of Medicine, Process Mining (PM) can be used to analyse healthcare-related data to infer the underlying diagnostic, treatment, and management processes. The PM paradigm provides techniques and tools to obtain information about the processes carried out by analysing the trace of healthcare events in the Electronic Health Records. In PM, workflows are the most frequent formalism used for representing the PM models. Despite the efforts to develop user-friendly tools, the understanding of PM models remains problematic. To improve this situation, we target the representation of PM models using ontologies. In this paper, we present a first version of the Clinical Process Model Ontology (CPMO), aimed at describing the sequential structure and associated metadata of PM models. Finally, we show the application of the CPMO to the domain of prostate cancer.

引用

页码：352 / 356

页数：5

共 12 条

[1] Braun Richard, 2014, 2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), P9, DOI 10.1109/BIBM.2014.6999261
[2] Ontology-Driven Extraction of Event Logs from Relational Databases
Calvanese, Diego
Montali, Marco
Syamsiyah, Alifah
van der Aalst, Wil M. P.
[J]. BUSINESS PROCESS MANAGEMENT WORKSHOPS, (BPM 2015), 2016, 256 : 140 - 153
[3] Semantic Web for Health Care and Life Sciences: a review of the state of the art
Cheung, Kei-Hoi
Prud'hommeaux, Eric
Wang, Yiming
Stephens, Susie
[J]. BRIEFINGS IN BIOINFORMATICS, 2009, 10 (02) : 111 - 113
[4] Fernandez-Llatas C., 2011, Proceedings of the 2011 5th Asia Modelling Symposium on Mathematical Modelling and Computer Simulation (AMS 2011), P56, DOI 10.1109/AMS.2011.22
[5] Fernandez-Llatas C., 2021, Interactive Process Mining in Healthcare, DOI [10.1007/978-3-030-53993-1, DOI 10.1007/978-3-030-53993-1, 10.1007/978- 3- 030-53993-1]
[6] Natschläger C, 2011, LECT NOTES BUS INF P, V95, P1
[7] BFO: Basic Formal Ontology
Otte, J. Neil
Beverley, John
Ruttenberg, Alan
[J]. APPLIED ONTOLOGY, 2022, 17 (01) : 17 - 43
[8] Process mining in healthcare: A literature review
Rojas, Eric
Munoz-Gama, Jorge
Sepulveda, Marcos
Capurro, Daniel
[J]. JOURNAL OF BIOMEDICAL INFORMATICS, 2016, 61 : 224 - 236
[9] Schulz S., 2013, GI-Jahrestagung, P1889
[10] Harmonizing SNOMED CT with BioTopLite: An Exercise in Principled Ontology Alignment
Schulz, Stefan
Martinez-Costa, Catalina
[J]. MEDINFO 2015: EHEALTH-ENABLED HEALTH, 2015, 216 : 832 - 836

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