Using Association Rules in Antimicrobial Resistance in Stone Disease Patients.

Ioannis Manolitsis,Georgios Feretzakis,Lazaros Tzelves,Dimitris Kalles,Evangelos Loupelis,Stamatis Katsimperis,Thanos Kosmidis,Athanasios Anastasiou,Dimitrios Koutsouris, Stavroula Kofopoulou,Vassilios S Verykios,Andreas Skolarikos,Ioannis Varkarakis

International Conference on Informatics, Management and Technology in Healthcare (ICIMTH)（2022）

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摘要

Association rule mining is a very popular unsupervised machine learning technique for discovering patterns in large datasets. Patients with stone disease commonly suffer from urinary tract infections (UTI), complicated by the emergence of antimicrobial resistance (AMR), due to the excessive use of antibiotics. In this study, we explore the use of association rule mining in the AMR profile of patients suffering from stone disease.

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关键词

AMR,Antimicrobial Resistance,Association rules,unsupervised ML

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