Stroke Risk Prediction with Machine Learning Techniques
Indexed incrossrefdoajpubmed
Abstract
A stroke is caused when blood flow to a part of the brain is stopped abruptly. Without the blood supply, the brain cells gradually die, and disability occurs depending on the area of the brain affected. Early recognition of symptoms can significantly carry valuable information for the prediction of stroke and promoting a healthy life. In this research work, with the aid of machine learning (ML), several models are developed and evaluated to design a robust framework for the long-term risk prediction of stroke occurrence. The main contribution of this study is a stacking method that achieves a high performance that is validated by various metrics, such as AUC, precision, recall, F-measure and accuracy. The…
Citation impact
276
total citations
- FWCI
- 21.16
- Percentile
- 100%
- References
- 68
Citations per year
Authors
2Topics & keywords
Topics
Keywords
- Stroke (engine)
- Machine learning
- Recall
- Computer science
- Artificial intelligence
- Measure (data warehouse)
- Precision and recall
- Stacking
No related works found for this paper.