Process mining and data mining applications in the domain of chronic diseases: A systematic review.
Chronic disease
Data mining
Process mining
Systematic review
Journal
Artificial intelligence in medicine
ISSN: 1873-2860
Titre abrégé: Artif Intell Med
Pays: Netherlands
ID NLM: 8915031
Informations de publication
Date de publication:
10 2023
10 2023
Historique:
received:
02
03
2023
revised:
24
08
2023
accepted:
28
08
2023
medline:
4
10
2023
pubmed:
3
10
2023
entrez:
2
10
2023
Statut:
ppublish
Résumé
The widespread use of information technology in healthcare leads to extensive data collection, which can be utilised to enhance patient care and manage chronic illnesses. Our objective is to summarise previous studies that have used data mining or process mining methods in the context of chronic diseases in order to identify research trends and future opportunities. The review covers articles that pertain to the application of data mining or process mining methods on chronic diseases that were published between 2000 and 2022. Articles were sourced from PubMed, Web of Science, EMBASE, and Google Scholar based on predetermined inclusion and exclusion criteria. A total of 71 articles met the inclusion criteria and were included in the review. Based on the literature review results, we detected a growing trend in the application of data mining methods in diabetes research. Additionally, a distinct increase in the use of process mining methods to model clinical pathways in cancer research was observed. Frequently, this takes the form of a collaborative integration of process mining, data mining, and traditional statistical methods. In light of this collaborative approach, the meticulous selection of statistical methods based on their underlying assumptions is essential when integrating these traditional methods with process mining and data mining methods. Another notable challenge is the lack of standardised guidelines for reporting process mining studies in the medical field. Furthermore, there is a pressing need to enhance the clinical interpretation of data mining and process mining results.
Identifiants
pubmed: 37783545
pii: S0933-3657(23)00159-8
doi: 10.1016/j.artmed.2023.102645
pii:
doi:
Types de publication
Systematic Review
Journal Article
Review
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
102645Informations de copyright
Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of competing interest Farhad Abtahi is the founder and CEO of Wergonic AB. Wergonic AB is a start-up company developing digital solutions for precision ergonomics.