Cargando…
Could the clinical interpretability of subgroups detected using clustering methods be improved by using a novel two-stage approach?
BACKGROUND: Recognition of homogeneous subgroups of patients can usefully improve prediction of their outcomes and the targeting of treatment. There are a number of research approaches that have been used to recognise homogeneity in such subgroups and to test their implications. One approach is to u...
Autores principales: | Kent, Peter, Stochkendahl, Mette Jensen, Christensen, Henrik Wulff, Kongsted, Alice |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4489132/ https://www.ncbi.nlm.nih.gov/pubmed/26140192 http://dx.doi.org/10.1186/s12998-015-0064-9 |
Ejemplares similares
-
Identifying clinical course patterns in SMS data using cluster analysis
por: Kent, Peter, et al.
Publicado: (2012) -
A comparison of three clustering methods for finding subgroups in MRI, SMS or clinical data: SPSS TwoStep Cluster analysis, Latent Gold and SNOB
por: Kent, Peter, et al.
Publicado: (2014) -
Identifying subgroups of patients using latent class analysis: should we use a single-stage or a two-stage approach? A methodological study using a cohort of patients with low back pain
por: Nielsen, Anne Molgaard, et al.
Publicado: (2017) -
How can latent trajectories of back pain be translated into defined subgroups?
por: Kongsted, Alice, et al.
Publicado: (2017) -
Contrasting real time quantitative measures (weekly SMS) to patients’ retrospective appraisal of their one-year’s course of low back pain; a probing mixed-methods study
por: Hestbaek, Lise, et al.
Publicado: (2019)