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Exploratory clustering for patient subpopulation discovery (CROSBI ID 647255)

Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija

Gamberger, Dragan ; Ženko, Bernard ; Lavrač, Nada Exploratory clustering for patient subpopulation discovery // Informatics for Health: Connected Citizen-Led Wellness and Population Health / Randell, Rebecca ; Cornet, Ronald ; McCowan, Colin et al. (ur.). IOS Press, 2017. str. 101-105

Podaci o odgovornosti

Gamberger, Dragan ; Ženko, Bernard ; Lavrač, Nada

engleski

Exploratory clustering for patient subpopulation discovery

Exploratory Clustering is a novel general purpose clustering tool which is especially appropriate for medical domains in which we need to identify subpopulations that are similar in two different data layers. The tool implements the multi-layer clustering algorithm in a framework that enables iterative experiments by the user in his search for relevant patient subpopulations. A unique property of the tool is integration of clustering and feature selection algorithms. Differences in values of most relevant attributes are used to demonstrate decisive properties of constructed clusters. Usefulness of the tool is illustrated on a task of discovering groups of patients with similar cognitive impairment.

Data clustering ; Biomarkers ; Alzheimer's disease

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Podaci o prilogu

101-105.

2017.

objavljeno

Podaci o matičnoj publikaciji

Informatics for Health: Connected Citizen-Led Wellness and Population Health

Randell, Rebecca ; Cornet, Ronald ; McCowan, Colin ; Peek, Niels ; Scott, Philip J. ;

IOS Press

978-1-61499-752-8

Podaci o skupu

Informatics for Health 2017

predavanje

24.04.2017-26.04.2017

Manchester, Ujedinjeno Kraljevstvo

Povezanost rada

Računarstvo