Dataciencia

Colección SciELO Chile

Innovative informatics methods for process mining in health care

Indexado

WoS	WOS:000870989100007
Scopus	SCOPUS_ID:85138583314

DOI

10.1016/J.JBI.2022.104203

Año

2022

Tipo

material editorial

Citas Totales

Autores Afiliación Chile

Instituciones Chile

% Participación
Internacional

Autores
Afiliación Extranjera

Instituciones
Extranjeras

Revista

Revista	ISSN
Journal Of Biomedical Informatics	1532-0464

Métricas Externas

PlumX	Altmetric	Dimensions

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Disciplinas de Investigación

WOS
Computer Science, Interdisciplinary Applications
Medical Informatics

Scopus
Sin Disciplinas

SciELO
Sin Disciplinas

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Publicaciones WoS (Ediciones: ISSHP, ISTP, AHCI, SSCI, SCI), Scopus, SciELO Chile.

Colaboración Institucional

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Autores - Afiliación

Ord.	Autor	Género	Institución - País
1	Munoz-Gama, Jorge	Hombre	Pontificia Universidad Católica de Chile - Chile
2	Martin, Niels	Hombre	Hasselt Univ - Bélgica Res Fdn Flanders FWO - Bélgica Universiteit Hasselt - Bélgica Research Foundation - Flanders - Bélgica
3	Fernandez-Llatas, Carlos	Hombre	Univ Politecn Valencia - España Karolinska Inst - Suecia Universitat Politècnica de València - España Karolinska Institutet - Suecia
4	Johnson, Owen A.	Hombre	UNIV LEEDS - Reino Unido University of Leeds - Reino Unido
5	SEPULVEDA-FERNANDEZ, MARCOS ERNESTO	Hombre	Pontificia Universidad Católica de Chile - Chile

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Financiamiento

Fuente
Sin Información

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Agradecimientos

Agradecimiento
This special issue is an initiative of the Process-Oriented Data Science for Healthcare Alliance, which is affiliated with the IEEE Task Force on Process Mining. The alliance aims to promote research and knowledge sharing between multidisciplinary stakeholders in the use of process mining approaches in the health care domain. The editors of this special issue would like to thank all reviewers for their valuable feedback, which certainly contributed towards improving the quality of the articles that were ultimately included in the special issue. Process mining is a discipline that bridges the gap between traditional process analysis and data-centric analysis. This discipline has gained popularity to analyze organizational and clinical health care processes. However, there is still a need for expanding the research in the field. The current world's most valuable resource is data. The biomedical and health domains can benefit from extracting valuable knowledge and insights from existing data. Regarding the execution of clinical processes, more and more data are being captured in the form of event data, which constitutes a key source of information to analyze and improve clinical processes. In this “Innovative Informatic methods for process mining in healthcare” editorial, we summarize twelve articles included in the special issue with the same name. These articles show a broad update on the state-of-the-art, challenges to be tackled, novel methodologies, requirements solved with techniques beyond classic process mining tasks and methods to provide easy-to-understand insights to doctors. These contributions are provided to researchers and practitioners interested in process mining applications for healthcare.

Agradecimiento

This special issue is an initiative of the Process-Oriented Data Science for Healthcare Alliance, which is affiliated with the IEEE Task Force on Process Mining. The alliance aims to promote research and knowledge sharing between multidisciplinary stakeholders in the use of process mining approaches in the health care domain. The editors of this special issue would like to thank all reviewers for their valuable feedback, which certainly contributed towards improving the quality of the articles that were ultimately included in the special issue. Process mining is a discipline that bridges the gap between traditional process analysis and data-centric analysis. This discipline has gained popularity to analyze organizational and clinical health care processes. However, there is still a need for expanding the research in the field. The current world's most valuable resource is data. The biomedical and health domains can benefit from extracting valuable knowledge and insights from existing data. Regarding the execution of clinical processes, more and more data are being captured in the form of event data, which constitutes a key source of information to analyze and improve clinical processes. In this “Innovative Informatic methods for process mining in healthcare” editorial, we summarize twelve articles included in the special issue with the same name. These articles show a broad update on the state-of-the-art, challenges to be tackled, novel methodologies, requirements solved with techniques beyond classic process mining tasks and methods to provide easy-to-understand insights to doctors. These contributions are provided to researchers and practitioners interested in process mining applications for healthcare.