2010
DOI: 10.1080/10934521003595290
|View full text |Cite
|
Sign up to set email alerts
|

Chemometric assessment of clinical data for diabetes mellitus 2 type patients using self-organizing maps

Abstract: The aim of this study was to offer an efficient and unsupervised strategy for medical data exploration to find relationships between clinical tests and major as well as concomitant syndromes of a specific disease. A large data set consisting of a group of 100 patients suffering diabetes mellitus type 2 disease characterized by more than 30 clinical parameters was explored using self-organizing maps (SOM) and classified by the use of non-hierarchical K-means algorithm implemented in the SOM. An attempt was made… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1

Citation Types

0
3
0

Year Published

2013
2013
2016
2016

Publication Types

Select...
2

Relationship

0
2

Authors

Journals

citations
Cited by 2 publications
(3 citation statements)
references
References 9 publications
0
3
0
Order By: Relevance
“…SOM analysis has been used in several medical studies. For example, Wickramasinghe et al (2011) and Astel et al (2010) showed that SOM techniques were useful for identifying patterns in patients with diabetes, and these results increased the possibility of developing specific strategies to manage these patients efficiently. SOM analyses have also been used to evaluate the efficacy of a specific screening for assessing the presence of infection in people (e.g., Sun et al 2011), showing better results than linear discriminant analysis.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…SOM analysis has been used in several medical studies. For example, Wickramasinghe et al (2011) and Astel et al (2010) showed that SOM techniques were useful for identifying patterns in patients with diabetes, and these results increased the possibility of developing specific strategies to manage these patients efficiently. SOM analyses have also been used to evaluate the efficacy of a specific screening for assessing the presence of infection in people (e.g., Sun et al 2011), showing better results than linear discriminant analysis.…”
Section: Discussionmentioning
confidence: 99%
“…), and they have to extract multiple data for their analysis. Thus, it is necessary to have efficient strategies to analyze and interpret these data from a multivariate perspective (Astel et al 2010). The use of visual data mining emerges as a technique that is able to provide high-quality information about the results obtained and the possibility of designing and developing strategies adapted to personal and clinical characteristics (Wickramasinghe et al 2011).…”
Section: Discussionmentioning
confidence: 99%
“…SOMs have also been used to classify patients with diseases. For example, Chen et al (2008) used an SOM to classify and visualize common characteristics in lung cancer patients for the purpose of predicting risk of disease, while Astel et al (2010) used an SOM to analyze the relationships between clinical tests and disease symptoms. In the field of education, SOMs have been used to classify types of e-learners in order to recommend appropriate online courses (Tai et al, 2008) and to cluster schools offering a Master of Business Administration degree in order to help students make decisions about which graduate schools to attend (Kiang and Fisher, 2008).…”
Section: The Sommentioning
confidence: 99%