Extracting Temporal Relationships in EHR: Application to COVID-19 Patients.
Stud Health Technol Inform
; 302: 546-550, 2023 May 18.
Article
in English
| MEDLINE | ID: covidwho-2325008
ABSTRACT
Association rules are one of the most used data mining techniques. The first proposals have considered relations over time in different ways, resulting in the so-called Temporal Association Rules (TAR). Although there are some proposals to extract association rules in OLAP systems, to the best of our knowledge, there is no method proposed to extract temporal association rules over multidimensional models in these kinds of systems. In this paper we study the adaptation of TAR to multidimensional structures, identifying the dimension that establishes the number of transactions and how to find time relative correlations between the other dimensions. A new method called COGtARE is presented as an extension of a previous approach proposed to reduce the complexity of the resulting set of association rules. The method is tested in application to COVID-19 patients data.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Algorithms
/
COVID-19
Type of study:
Reviews
Limits:
Humans
Language:
English
Journal:
Stud Health Technol Inform
Journal subject:
Medical Informatics
/
Health Services Research
Year:
2023
Document Type:
Article
Affiliation country:
Shti230202
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