• Tanmay Pandit
• Vaibhav Khurana
• Neha Dudhane
• Vaishnav Nandre

Machine Learning is that the procedure of data assessing from different perspectives and uniting into helpful data. This system is employed for locating CV disease. Supported risk factor the cardiovascular diseases are often defined very easily. The first point of this work is to assess diverse grouping strategies in heart determination. First, the numeric dataset is extracted and pre process them. Then using extract the features that’s condition to be find to be classified by machine learning. Compared to existing; machine learning provides better performance. After Classification, execution standards including precision, accuracy, F-measure is to be determined. Machine Learning gives better execution. The comparison measure expose that Random Forest is that the best classifier for the diagnosis of cardiovascular (CV) disease on the prevailing dataset.

High-risk prediction, deep neural network, attention mechanism, cardiovascular diseases.High-risk prediction, deep neural network, attention mechanism, cardiovascular diseases.

"High Risk Assessment in cardiovascular diseases using machine learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 6, page no.a965-a968, June-2021, Available :http://www.jetir.org/papers/JETIR2106137.pdf

"High Risk Assessment in cardiovascular diseases using machine learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 6, page no. ppa965-a968, June-2021, Available at : http://www.jetir.org/papers/JETIR2106137.pdf