• Ms. Raunak Masih
• Mr.Ramratan Ahirwal

The medical discipline is divided into various sub-fields, each with its own diagnostic techniques. Nonetheless, in projecting the future of drugs and patient health, machine learning is becoming increasingly crucial. This is due to the trustworthiness of the various classification techniques. Because of the influence of numerous data retrieved from patients, reliable cardiac disease prediction is becoming increasingly difficult, and separating these components is a critical research issue. Higher performance can be achieved by introducing individual classification algorithms and ensemble learning approaches, which lead to accurate prediction of atherosclerosis disorders. For the purpose to increase the classification result accuracy rate of Atherosclerosis Diseases, heterogeneity of machine learning algorithms, also include their related problems and performance results; have been investigated in this work. Several symptoms that directly or indirectly suggest atherosclerosis (cardiovascular disease), as well as several modifiable and non-modifiable peril factors for athero disease and several forms of athero (heart) diseases with their causes of failures, have been examined in greater detail. The goal of all of these publications is to improve accuracy and make the system more efficient so that it can more accurately forecast attack probability. The results reveal improved performance in terms of performance measures and provide a better knowledge of the accuracy, dependability, and utility of the classifier models.

Atherosclerosis Diseases, Supervised Learning Algorithms, Machine Learning Algorithms, Performance measures.

"A Review of Atherosclerosis Disease Prediction Using Machine Learning Algorithms", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 5, page no.k606-k613, May-2022, Available :http://www.jetir.org/papers/JETIR2205B78.pdf

"A Review of Atherosclerosis Disease Prediction Using Machine Learning Algorithms", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 5, page no. ppk606-k613, May-2022, Available at : http://www.jetir.org/papers/JETIR2205B78.pdf