Prediction of Pathological Subjects Using Genetic Algorithms
Joint Authors
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-01-29
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
This paper aims at estimating pathological subjects from a population through various physical information using genetic algorithm (GA).
For comparison purposes, K-Means (KM) clustering algorithm has also been used for the estimation.
Dataset consisting of some physical factors (age, weight, and height) and tibial rotation values was provided from the literature.
Tibial rotation types are four groups as RTER, RTIR, LTER, and LTIR.
Each tibial rotation group is divided into three types.
Narrow (Type 1) and wide (Type 3) angular values were called pathological and normal (Type 2) angular values were called nonpathological.
Physical information was used to examine if the tibial rotations of the subjects were pathological.
Since the GA starts randomly and walks all solution space, the GA is seen to produce far better results than the KM for clustering and optimizing the tibial rotation data assessments with large number of subjects even though the KM algorithm has similar effect with the GA in clustering with a small number of subjects.
These findings are discovered to be very useful for all health workers such as physiotherapists and orthopedists, in which this consequence is expected to help clinicians in organizing proper treatment programs for patients.
American Psychological Association (APA)
Sari, Murat& Tuna, Can. 2018. Prediction of Pathological Subjects Using Genetic Algorithms. Computational and Mathematical Methods in Medicine،Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1132077
Modern Language Association (MLA)
Sari, Murat& Tuna, Can. Prediction of Pathological Subjects Using Genetic Algorithms. Computational and Mathematical Methods in Medicine No. 2018 (2018), pp.1-9.
https://search.emarefa.net/detail/BIM-1132077
American Medical Association (AMA)
Sari, Murat& Tuna, Can. Prediction of Pathological Subjects Using Genetic Algorithms. Computational and Mathematical Methods in Medicine. 2018. Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1132077
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1132077