Current cardiovascular risk assessment tools use a small number of predictors. Here, we
study how machine learning might:(1) enable principled selection from a large multimodal …

Abstract Purposes Cardiovascular diseases (CVDs) are the most prominent killer in the
twenty-first century. The success of promising therapeutics for CVDs is challenging, as …

Develo** risk assessment tools for CAD prediction remains challenging nowadays. We
developed an ML predictive algorithm based on metabolic and clinical data for determining …

Abstract Machine learning has become a salient part of our life nowadays. It has a significant
effect on the medical decision support system also. In the healthcare domain, it is beneficial …

Atheromatic plaque progression is considered as a typical pathological condition of arteries
and although atherosclerosis is considered as a systemic inflammatory disorder …

To predict cardiovascular complications, it is proposed to use “weak” classifiers with virtual
flows. The “weak” classifier is based on studies of electrical conductivity at biologically active …

Cardiovascular diseases (CVDs) are prevalent in the population and often lead to fatalities.
Recent polls indicate that the death rate is increasing due to people's increased use of …

Page 1 AHFE International Jay Kalra Editor VIXXXX IM Volume 78 Health Informatics and
Biomedical Engineering Applications Proceedings of the 14th International Conference on …

During the last decade, the life span of the world has been incremented year by year, which
comes with a higher probability of suffering from an illness related to aging. An example of …

Cardiovascular disease (CVD), a global disability problem, accounts for 46% of mortality in
Iran. Prediction of cardiovascular disease risk factors can help in early diagnosis, decision …