The aim of this study was to identify, with soft clustering methods, multimorbidity patterns in the electronic health records of a population =65 years, and to analyse such patterns in accordance with the different prevalence cut-off points applied. Fuzzy cluster analysis allows individuals to be linked simultaneously to multiple clusters and is more consistent with clinical experience than other approaches frequently found in the literature.Peer Reviewe
Background: Hospital care organization, structured around medical specialties and focused on the sep...
Multimorbidity is present in more than one quarter of the population in Australia, and its prevalenc...
(1) Background: The acquisition of multiple chronic diseases, known as multimorbidity, is common in ...
The aim of this study was to identify, with soft clustering methods, multimorbidity patterns in the ...
Objectives: the aim of this study was to identify, with soft clustering methods, multimorbidity patt...
Altres ajuts: PERIS/SLT002/16/00058Objectives The aim of this study was to identify, with soft clust...
Our purpose in this article is to describe and illustrate the application of cluster analysis to ide...
Our purpose in this article is to describe and illustrate the application of clus-ter analysis to id...
Abstract Background Multimorbidity is the coexistence of more than two chronic diseases in the same ...
Abstract Background The purpose of this study was to ascertain multimorbidity patterns using a non-h...
Multimorbidity is a common problem in the elderly that is significantly associated with higher morta...
The purpose of this study was to identify clusters of diagnoses in elderly patients with multimorbid...
OBJECTIVE: Multimorbidity is a common problem in the elderly that is significantly associated with h...
Clustering is one of the most used tools in data analysis. In the last decades, due to the increasin...
Multimorbidity—the co-occurrence of multiple diseases—is associated to poor prognosis, but the scarc...
Background: Hospital care organization, structured around medical specialties and focused on the sep...
Multimorbidity is present in more than one quarter of the population in Australia, and its prevalenc...
(1) Background: The acquisition of multiple chronic diseases, known as multimorbidity, is common in ...
The aim of this study was to identify, with soft clustering methods, multimorbidity patterns in the ...
Objectives: the aim of this study was to identify, with soft clustering methods, multimorbidity patt...
Altres ajuts: PERIS/SLT002/16/00058Objectives The aim of this study was to identify, with soft clust...
Our purpose in this article is to describe and illustrate the application of cluster analysis to ide...
Our purpose in this article is to describe and illustrate the application of clus-ter analysis to id...
Abstract Background Multimorbidity is the coexistence of more than two chronic diseases in the same ...
Abstract Background The purpose of this study was to ascertain multimorbidity patterns using a non-h...
Multimorbidity is a common problem in the elderly that is significantly associated with higher morta...
The purpose of this study was to identify clusters of diagnoses in elderly patients with multimorbid...
OBJECTIVE: Multimorbidity is a common problem in the elderly that is significantly associated with h...
Clustering is one of the most used tools in data analysis. In the last decades, due to the increasin...
Multimorbidity—the co-occurrence of multiple diseases—is associated to poor prognosis, but the scarc...
Background: Hospital care organization, structured around medical specialties and focused on the sep...
Multimorbidity is present in more than one quarter of the population in Australia, and its prevalenc...
(1) Background: The acquisition of multiple chronic diseases, known as multimorbidity, is common in ...