Analysis of significant factors for dengue infection prognosis using the self organizing map

Faisal, T. and Ibrahim, F. and Taib, M.N. (2008) Analysis of significant factors for dengue infection prognosis using the self organizing map. Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference, 2008. pp. 5140-5143. ISSN 1557170X

[img]
Preview
PDF (Analysis of significant factors for dengue infection prognosis using the self organizing map)
Analysis_of_significant_factors_for_dengue_infection_prognosis_using_the_self_organizing_map.pdf - Published Version

Download (247kB)
Official URL: http://www.scopus.com/inward/record.url?eid=2-s2.0...

Abstract

This study presents a new approach to determine the significant prognosis factors in dengue patients utilizing the self-organizing map (SOM). SOM was used to visualize and determine the significant factors that can differentiate between the dengue patients and the healthy subjects. Bioimpedance analysis (BIA) parameters and symptoms/signs obtained from the 210 dengue patients during their hospitalization were used in this study. Database comprised of 329 sample (210 dengue patients and 119 healthy subjects) were used in the study. Accordingly, two maps were constructed. A total of 35 predictors (17 BIA parameters, 18 symptoms/signs) were investigated on the day of defervescence of fever. The first map was constructed based on BIA parameters while the second map utilized the symptoms and signs. The visualized results indicated that, the significant BIA prognosis factors for differentiating the dengue patients from the healthy subjects are reactance, intracellular water, ratio of the extracellular water and intracellular water, and ratio of the extracellular mass and body cell mass.

Item Type: Article
Additional Information: Export Date: 29 January 2014 Source: Scopus PubMed ID: 19163874 Language of Original Document: English Correspondence Address: Faisal, T.
Uncontrolled Keywords: Algorithm, Article, computer assisted diagnosis, decision support system, dengue, human, Malaysia, Methodology, proportional hazards model, risk assessment, risk factor, Algorithms, Decision Support Systems, Clinical, Diagnosis, Computer-Assisted, Humans, Proportional Hazards Models, Risk Factors
Subjects: T Technology > T Technology (General)
T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Engineering
Depositing User: Mr Jenal S
Date Deposited: 26 Mar 2014 02:16
Last Modified: 01 Nov 2017 05:43
URI: http://eprints.um.edu.my/id/eprint/9258

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year