Cardiovascular Events
Cardiovascular events refer to acute or chronic manifestations of Cardiovascular Disease (CVD), including myocardial infarction, stroke, and heart failure. CVD remains a leading cause of mortality globally, with significant burden driven by aging populations and comorbidities.
Key Statistics & Burden
- CVD accounted for nearly 900,000 deaths in the US alone in 2016 1.
- The burden of CVD is projected to rise due to demographic shifts and increased prevalence of risk factors.
Predictive Modeling & Machine Learning
Recent advancements leverage machine-learning and Artificial Intelligence to improve risk stratification and early detection.
- Statistical Inference at Population Level: Research by Brijesh Patel and Partho Sengupta (IEEE, 2016) elucidates methods for statistical inference using representative sampling.
- Prediction Algorithms: ML models are increasingly used to predict adverse cardiovascular outcomes, addressing the limitations of traditional risk scores.
- See detailed analysis in: Patel - Machine learning for predicting cardiac events
References
- ^1 Patel, B., & Sengupta, P. (2016). Elucidating statistical inferences at the population level using representative sampling. IEEE. DOI: 10.1080/14779072.2020.1732208