Affiliation:
1. Mtech Scholar RITS, Bhopal, Madhya Pradesh, India
2. Professor, RITS, Bhopal, Madhya Pradesh, India
Abstract
Globally, cardiovascular disease is the leading cause of death, according to WHO (World Health Organization) data, with more people dying from CVDs each year than any other cause. In 2016, an estimated 17.9 million people died as a result of cardiovascular disease (CVD), accounting for 31% of all deaths worldwide. A heart attack or a stroke is to blame for the majority of these deaths, at around 85%. Low- and middle-income countries account for nearly three-quarters of deaths from cardiovascular disease (CVD). A staggering 82% of the 17 million non-communicable disease-related deaths in 2015 occurred in countries with low or middle incomes, with cardiovascular disease accounting for 37% of all deaths under the age of 70. Tobacco use, an unhealthy diet, obesity, inactivity, and harmful use of alcohol can all be addressed through population-wide strategies to prevent most cardiovascular diseases [1].
Reference24 articles.
1. C. S. Prakash, M. Madhu Bala and A. Rudra, "Data Science Framework - Heart Disease Predictions, Variant Models and Visualizations," 2020 International Conference on Computer Science, Engineering and Applications (ICCSEA), Gunupur, India, 2020, pp. 1-4.
2. M. Fatima, M. Pasha” Survey of Machine Learning Algorithms for Disease Diagnostic” Journal of Intelligent Learning Systems and Applications, 2017, 9, 1-16
3. V.V. Ramalingam, Ayantan Dandapath, M Karthik Raja “Heart disease prediction using machine learning techniques: A Survey” International Journal of Engineering & Technology, 7 (2.8), 2018, 684-687
4. Mr. Chala Beyene, Pooja Kamat ”Survey on Prediction and Analysis the Occurrence of Heart Disease Using Data Mining Techniques” International Journal of Pure and Applied Mathematics , ijpam Volume 118 No. 8 ,2018, 165-174
5. N. Satish Chandra Reddy, Song Shue Nee, Lim Zhi Min & Chew Xin Ying” Classification and Feature Selection Approaches by Machine Learning Techniques: Heart Disease Prediction.”International Journal of Innovative Computing , IJIC Vol. 9:1, 2019,39-46