Classification models combined with Boruta feature selection for heart disease prediction
SASTRA University · Obuda University · +1 more institution
Abstract
Cardiovascular disease (CVD), generally called heart illness, is a collective term for various ailments that affect the heart and blood vessels. Heart disease is a primary cause of fatality and morbidity in people worldwide, resulting in 18 million deaths per year. By identifying those who are most vulnerable to heart diseases and ensuring they receive the appropriate care, premature demise can be prevented. Machine learning algorithms are now crucial in the medical field, especially when using medical databases to diagnose diseases. Such efficient algorithms and data processing techniques are applied to predict various diseases and offer much potential for accurate heart disease prognosis. Therefore, this…
Citation impact
- FWCI
- 79.75
- Percentile
- 100%
- References
- 34
Authors
6Topics & keywords
- Feature selection
- Support vector machine
- Logistic regression
- Artificial intelligence
- Machine learning
- Computer science
- Heart disease
- Decision tree
- Good health and well-being