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Title: :  Myocardial Infraction Predication using Machine Learning
PaperId: :  20003
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 9 Issue 3 2023
DUI:    16.0415/IJARIIE-20003
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Priya Darshini SAnand Institute of Higher Technology
Mounica Manasa PAnand Institute of Higher Technology
Naveen Kumar VAnand Institute of Higher Technology
Maheswari MAnand Institute of Higher Technology
Dr. Roselin Mary SAnand Institute of Higher Technology

Abstract

Computer Science Engineering
Machine Learning (ML), Features, Classifiers , Myocardial Infraction (MI), Electrocardiogram (ECG),Logistic Regression (LR)
Heart disease is one of the complex diseases and globally many people suffered from this disease. On time and efficient identification of heart disease plays a key role in healthcare, particularly in the field of cardiology. We proposed an efficient and accurate system to diagnosis heart disease and the system is based on machine learning techniques. The system is developed based on classification algorithms includes Support vector machine, Logistic regression, Artificial neural network, K-nearest neighbor, Naïve bays, and Decision tree while standard features selection algorithms. The research paper mainly focuses on which patient is more likely to have a heart disease based on various medical attributes. We prepared a heart disease prediction system to predict whether the patient is likely to be diagnosed with a heart disease or not using the medical history of the patient. The strength of the proposed model was quiet satisfying and was able to predict evidence of having a heart disease in a particular individual by using random forest, KNN and Logistic Regression which showed a good accuracy in comparison which is used prediction. So, a quiet significant amount of pressure has been lift off by using the given model in finding the probability of the classifier to correctly and accurately identify the heart disease and got 91% Accuracy.

Citations

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IJARIIE Priya Darshini S, Mounica Manasa P, Naveen Kumar V, Maheswari M, and Dr. Roselin Mary S. "Myocardial Infraction Predication using Machine Learning" International Journal Of Advance Research And Innovative Ideas In Education Volume 9 Issue 3 2023 Page 10-16
MLA Priya Darshini S, Mounica Manasa P, Naveen Kumar V, Maheswari M, and Dr. Roselin Mary S. "Myocardial Infraction Predication using Machine Learning." International Journal Of Advance Research And Innovative Ideas In Education 9.3(2023) : 10-16.
APA Priya Darshini S, Mounica Manasa P, Naveen Kumar V, Maheswari M, & Dr. Roselin Mary S. (2023). Myocardial Infraction Predication using Machine Learning. International Journal Of Advance Research And Innovative Ideas In Education, 9(3), 10-16.
Chicago Priya Darshini S, Mounica Manasa P, Naveen Kumar V, Maheswari M, and Dr. Roselin Mary S. "Myocardial Infraction Predication using Machine Learning." International Journal Of Advance Research And Innovative Ideas In Education 9, no. 3 (2023) : 10-16.
Oxford Priya Darshini S, Mounica Manasa P, Naveen Kumar V, Maheswari M, and Dr. Roselin Mary S. 'Myocardial Infraction Predication using Machine Learning', International Journal Of Advance Research And Innovative Ideas In Education, vol. 9, no. 3, 2023, p. 10-16. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/Myocardial_Infraction_Predication_using_Machine__Learning_ijariie20003.pdf (Accessed : ).
Harvard Priya Darshini S, Mounica Manasa P, Naveen Kumar V, Maheswari M, and Dr. Roselin Mary S. (2023) 'Myocardial Infraction Predication using Machine Learning', International Journal Of Advance Research And Innovative Ideas In Education, 9(3), pp. 10-16IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/Myocardial_Infraction_Predication_using_Machine__Learning_ijariie20003.pdf (Accessed : )
IEEE Priya Darshini S, Mounica Manasa P, Naveen Kumar V, Maheswari M, and Dr. Roselin Mary S, "Myocardial Infraction Predication using Machine Learning," International Journal Of Advance Research And Innovative Ideas In Education, vol. 9, no. 3, pp. 10-16, May-Jun 2023. [Online]. Available: https://ijariie.com/AdminUploadPdf/Myocardial_Infraction_Predication_using_Machine__Learning_ijariie20003.pdf [Accessed : ].
Turabian Priya Darshini S, Mounica Manasa P, Naveen Kumar V, Maheswari M, and Dr. Roselin Mary S. "Myocardial Infraction Predication using Machine Learning." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 9 number 3 ().
Vancouver Priya Darshini S, Mounica Manasa P, Naveen Kumar V, Maheswari M, and Dr. Roselin Mary S. Myocardial Infraction Predication using Machine Learning. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2023 [Cited : ]; 9(3) : 10-16. Available from: https://ijariie.com/AdminUploadPdf/Myocardial_Infraction_Predication_using_Machine__Learning_ijariie20003.pdf
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