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Extracting Temporal Relationships in EHR: Application to COVID-19 Patients.
Molina, Carlos; Prados-Suarez, Belén.
  • Molina C; Department of Software Engineering, University of Granada, Spain.
  • Prados-Suarez B; Department of Software Engineering, University of Granada, Spain.
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.
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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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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