Clustering of patients' trajectories with an auto-stopped bisecting K-Medoids algorithm

DOI10.1007/s10852-012-9198-0zbMath1311.62092OpenAlexW2015032625MaRDI QIDQ367245

Nadine Meskens, Hongying Fei

Publication date: 26 September 2013

Published in: Journal of Mathematical Modelling and Algorithms in Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10852-012-9198-0

zbMATH Keywords

clustering algorithmbisecting K-Medoidspatient trajectories

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Uses Software

• clusfind

Cites Work

• Unnamed Item
• Clustering rules: A comparison of partitioning and hierarchical clustering algorithms
• A graph b-coloring framework for data clustering
• Finding Groups in Data

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