Fetal Cardiac Structure Identification Using Genetic Algorithm with K Means Clustering
M. Manikandan1, N. V. Andrews2
1M. Manikandan, Department of Electronics and Communication Engineering, M. Kumarasamy College Engineering, Karur (Tamil Nadu), India.
2N. V. Andrews, Department of Electronics and Communication Engineering, M. Kumarasamy College Engineering, Karur (Tamil Nadu), India.
Manuscript received on 27 April 2019 | Revised Manuscript received on 09 May 2019 | Manuscript Published on 17 May 2019 | PP: 548-551 | Volume-7 Issue-6S4 April 2019 | Retrieval Number: F11150476S419/2019©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Fetal cardiac estimation is more important for cardiac anomalies of the infant. The infant mortality rate can be estimate from the measurement of cardiac structure during the trimester and fifth month of pregnancy. In this paper the novel method is used to estimate the cardiac structure using genetic algorithm (GA). GA has the efficient computation tool for finding the best fittest value by mutation process. After the estimation the cardiac disease can be found with normal cardiac parameters. This idea is very useful for the physician to diagnosis the Congenital Heart Disease (CHD). The above methodology address the various examinations associated with Cardiac molarities from birth to death.
Keywords: Genetic Algorithm, Cardiac Anomalies, K Means Clustering.
Scope of the Article: Algorithm Engineering