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A Novel Clinical Decision Support System Using Improved Adaptive Genetic Algorithm for the Assessment of Fetal Well-Being
Joint Authors
Ravindran, Sindhu
Jambek, Asral Bahari
Muthusamy, Hariharan
Neoh, Siew-Chin
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-02-22
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
A novel clinical decision support system is proposed in this paper for evaluating the fetal well-being from the cardiotocogram (CTG) dataset through an Improved Adaptive Genetic Algorithm (IAGA) and Extreme Learning Machine (ELM).
IAGA employs a new scaling technique (called sigma scaling) to avoid premature convergence and applies adaptive crossover and mutation techniques with masking concepts to enhance population diversity.
Also, this search algorithm utilizes three different fitness functions (two single objective fitness functions and multi-objective fitness function) to assess its performance.
The classification results unfold that promising classification accuracy of 94% is obtained with an optimal feature subset using IAGA.
Also, the classification results are compared with those of other Feature Reduction techniques to substantiate its exhaustive search towards the global optimum.
Besides, five other benchmark datasets are used to gauge the strength of the proposed IAGA algorithm.
American Psychological Association (APA)
Ravindran, Sindhu& Jambek, Asral Bahari& Muthusamy, Hariharan& Neoh, Siew-Chin. 2015. A Novel Clinical Decision Support System Using Improved Adaptive Genetic Algorithm for the Assessment of Fetal Well-Being. Computational and Mathematical Methods in Medicine،Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1057854
Modern Language Association (MLA)
Ravindran, Sindhu…[et al.]. A Novel Clinical Decision Support System Using Improved Adaptive Genetic Algorithm for the Assessment of Fetal Well-Being. Computational and Mathematical Methods in Medicine No. 2015 (2015), pp.1-11.
https://search.emarefa.net/detail/BIM-1057854
American Medical Association (AMA)
Ravindran, Sindhu& Jambek, Asral Bahari& Muthusamy, Hariharan& Neoh, Siew-Chin. A Novel Clinical Decision Support System Using Improved Adaptive Genetic Algorithm for the Assessment of Fetal Well-Being. Computational and Mathematical Methods in Medicine. 2015. Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1057854
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1057854