Effective Heart Disease Prediction Using Machine Learning Techniques
Pandit Deendayal Energy University · National Research Council
Abstract
The diagnosis and prognosis of cardiovascular disease are crucial medical tasks to ensure correct classification, which helps cardiologists provide proper treatment to the patient. Machine learning applications in the medical niche have increased as they can recognize patterns from data. Using machine learning to classify cardiovascular disease occurrence can help diagnosticians reduce misdiagnosis. This research develops a model that can correctly predict cardiovascular diseases to reduce the fatality caused by cardiovascular diseases. This paper proposes a method of k-modes clustering with Huang starting that can improve classification accuracy. Models such as random forest (RF), decision tree classifier…
Citation impact
- FWCI
- 174.25
- Percentile
- 100%
- References
- 39
Authors
4Topics & keywords
- Random forest
- Cross-validation
- Computer science
- Decision tree
- Artificial intelligence
- Machine learning
- Multilayer perceptron
- Classifier (UML)