ISSN 2394-5125
 

Research Article 


MACHINE LEARNING CLASSIFIER AND NEURAL MODELLING PERSPECTIVE OF ECHOCARDIOGRAPHY FOR THALASSEMIA PATIENTS IN CONTEXT TO PEDIATRIC AGE GROUP

Aditya Maheshwari,Prasun Chakrabarti.

Abstract
The paper indicates the rate of growth of thalassemia with corresponding sex bifurcation. The total number of blood transfusions with respect to ferritin, frequency (In months), Height, weight, eco have been analysed based on the graphical representation. It has been observed that chest x rate in case of male corresponding to EF_Normal is maximum as a specific instant of time. In the case of inference (Age: 5-15 Months Thalassemia is dominant). Relevant Neural network has been designed using 7 hidden layer neurons whereby achieving 92.67% accuracy rate. Among all the Machine learning classifier Random Forest Tree is the optimum one.

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Pubmed Style

Aditya Maheshwari ,Prasun Chakrabarti. MACHINE LEARNING CLASSIFIER AND NEURAL MODELLING PERSPECTIVE OF ECHOCARDIOGRAPHY FOR THALASSEMIA PATIENTS IN CONTEXT TO PEDIATRIC AGE GROUP. JCR. 2020; 7(9): 1144-1149. doi:10.31838/jcr.07.09.210


Web Style

Aditya Maheshwari ,Prasun Chakrabarti. MACHINE LEARNING CLASSIFIER AND NEURAL MODELLING PERSPECTIVE OF ECHOCARDIOGRAPHY FOR THALASSEMIA PATIENTS IN CONTEXT TO PEDIATRIC AGE GROUP. http://www.jcreview.com/?mno=115815 [Access: May 30, 2021]. doi:10.31838/jcr.07.09.210


AMA (American Medical Association) Style

Aditya Maheshwari ,Prasun Chakrabarti. MACHINE LEARNING CLASSIFIER AND NEURAL MODELLING PERSPECTIVE OF ECHOCARDIOGRAPHY FOR THALASSEMIA PATIENTS IN CONTEXT TO PEDIATRIC AGE GROUP. JCR. 2020; 7(9): 1144-1149. doi:10.31838/jcr.07.09.210



Vancouver/ICMJE Style

Aditya Maheshwari ,Prasun Chakrabarti. MACHINE LEARNING CLASSIFIER AND NEURAL MODELLING PERSPECTIVE OF ECHOCARDIOGRAPHY FOR THALASSEMIA PATIENTS IN CONTEXT TO PEDIATRIC AGE GROUP. JCR. (2020), [cited May 30, 2021]; 7(9): 1144-1149. doi:10.31838/jcr.07.09.210



Harvard Style

Aditya Maheshwari ,Prasun Chakrabarti (2020) MACHINE LEARNING CLASSIFIER AND NEURAL MODELLING PERSPECTIVE OF ECHOCARDIOGRAPHY FOR THALASSEMIA PATIENTS IN CONTEXT TO PEDIATRIC AGE GROUP. JCR, 7 (9), 1144-1149. doi:10.31838/jcr.07.09.210



Turabian Style

Aditya Maheshwari ,Prasun Chakrabarti. 2020. MACHINE LEARNING CLASSIFIER AND NEURAL MODELLING PERSPECTIVE OF ECHOCARDIOGRAPHY FOR THALASSEMIA PATIENTS IN CONTEXT TO PEDIATRIC AGE GROUP. Journal of Critical Reviews, 7 (9), 1144-1149. doi:10.31838/jcr.07.09.210



Chicago Style

Aditya Maheshwari ,Prasun Chakrabarti. "MACHINE LEARNING CLASSIFIER AND NEURAL MODELLING PERSPECTIVE OF ECHOCARDIOGRAPHY FOR THALASSEMIA PATIENTS IN CONTEXT TO PEDIATRIC AGE GROUP." Journal of Critical Reviews 7 (2020), 1144-1149. doi:10.31838/jcr.07.09.210



MLA (The Modern Language Association) Style

Aditya Maheshwari ,Prasun Chakrabarti. "MACHINE LEARNING CLASSIFIER AND NEURAL MODELLING PERSPECTIVE OF ECHOCARDIOGRAPHY FOR THALASSEMIA PATIENTS IN CONTEXT TO PEDIATRIC AGE GROUP." Journal of Critical Reviews 7.9 (2020), 1144-1149. Print. doi:10.31838/jcr.07.09.210



APA (American Psychological Association) Style

Aditya Maheshwari ,Prasun Chakrabarti (2020) MACHINE LEARNING CLASSIFIER AND NEURAL MODELLING PERSPECTIVE OF ECHOCARDIOGRAPHY FOR THALASSEMIA PATIENTS IN CONTEXT TO PEDIATRIC AGE GROUP. Journal of Critical Reviews, 7 (9), 1144-1149. doi:10.31838/jcr.07.09.210