Efficient Algorithms for Patterns Identification in Medical Data-Reference-Cited by-同舟云学术

Efficient Algorithms for Patterns Identification in Medical Data

Published:2023-06-01 Issue:1 Volume:20 Page:32-36
ISSN:2668-4217
Container-title:Acta Marisiensis. Seria Technologica
language:en
Short-container-title:

Author:

Calin Avram¹,Gligor Adrian¹,Nylas Victoria¹,Dumitru Roman²

Affiliation:

1. George Emil Palade University of Medicine , Pharmacy, Science and Technology of Targu Mures , Gh. Marinescu, 38, Târgu Mureș, Mureș, 540142 , Romania

2. Sintef Forskningsveien 1, 0373 Oslo , Norway

Abstract

Abstract Recently, medical databases have expanded rapidly, and the amount of information is huge. This abundance of data appears as a consequence of the new technologies that have been developed in the medical field and that allow easy data collection. The performance of the technique depends on the input data and available resources. Whereas, in Eclat the repeated scanning of the database is eliminated and consumes less time and we can conclude that Eclat is better than Apriori and Fpgrowth. If we refer to the execution time and memory usage, then the FP-Growth algorithm is more efficient than the Eclat algorithm or the Apriori algorithm. If we consider factor other than time, the result may vary from one factor to another.

Publisher

Walter de Gruyter GmbH

Link

https://www.sciendo.com/pdf/10.2478/amset-2023-0006

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