Cardiac disease is the main outstanding reason for death over the humankind. The main reason of cardiac attack is lead to be the blockage of blood vessels, chest pain or stroke, it is mainly caused the blood clotting in arteries, due to this some patients have unstable angina. This disease could be a diagnosis by the prediction and detection of patient history records the current Status of Patients. It is mainly due to when the heart is not properly working and unable to supply the amount of blood in the blood vessels. It is the most essential organ of the individual body. Heart disease (HD) detection could be calculated by different datasets that are relating to medical parameters that provide to the cardiology related information. The big challenge is the shortage of physicians, experts that may arise the death, and patient disability. For analysis it needs an expert system that discovers their related hidden patterns for the heart disease envision using medical data. One of the most cognitive procedures that are data mining which is used the patterns of huge datasets by the hidden approach. This paper presents the survey and comparative analysis on Heart Disease prediction using various ML approach. This study helps us to know the existing technologies to cure Heart Disease as well as the best technology in terms of accuracy rate. In this paper with the help of different Machine learning Algorithms different works is compared.
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Research Article| March 21 2022
An automated perception and prediction of heart disease based on machine learning
AIP Conf. Proc. 2424, 020001 (2022)
Ritu Aggarwal, Suneet Kumar; An automated perception and prediction of heart disease based on machine learning. AIP Conf. Proc. 21 March 2022; 2424 (1): 020001. https://doi.org/10.1063/5.0076788
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