Routinely collected electronic health records (EHRs) data contain a vast amount of valuable
information for conducting epidemiological studies. With the right tools, we can gain insights …

Machine learning (ML) and large-scale big data are key factors in developing an accurate
prediction model for cardiovascular disease (CVD). Although the CVD risk often depends on …

Cardiovascular disease (CVD) is the leading cause of death worldwide and is a global
health issue. Traditionally, statistical models are used commonly in the risk prediction and …

There is a considerable rise in cardiovascular diseases in the world. It is pertinently
essential to make cardiovascular prediction accurate to the maximum. A forecast based on …

Artificial intelligence (AI) broadly refers to analytical algorithms that iteratively learn from
data, allowing computers to find hidden insights without being explicitly programmed where …

Heart disease is one of the major causes of life complicacies and subsequently leading to
death. The heart disease diagnosis and treatment are very complex, especially in the …

Cardiovascular disease is the leading cause of global mortality and responsible for millions
of deaths annually. The mortality rate and overall consequences of cardiac disease can be …

Provenance: This is an invited article commissioned by the Editorial Office, Annals of
Translational Medicine. Comment on: Zhou ZR, Wang WW, Li Y, et al. In-depth mining of …

Introduction Data based on electronic health records (EHRs) are rich with individual-level
longitudinal measurement information and are becoming an increasingly common data …

Background In the broader healthcare domain, the prediction bears more value than an
explanation considering the cost of delays in its services. There are various risk prediction …