AIMC Topic: Cardiovascular Diseases

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Modeling time-to-event (survival) data using classification tree analysis.

Journal of evaluation in clinical practice
RATIONALE, AIMS, AND OBJECTIVES: Time to the occurrence of an event is often studied in health research. Survival analysis differs from other designs in that follow-up times for individuals who do not experience the event by the end of the study (cal...

Cardiovascular events in patients with mild autonomous cortisol secretion: analysis with artificial neural networks.

European journal of endocrinology
BACKGROUND: The independent role of mild autonomous cortisol secretion (ACS) in influencing the cardiovascular event (CVE) occurrence is a topic of interest. We investigated the role of mild ACS in the CVE occurrence in patients with adrenal incident...

Can machine-learning improve cardiovascular risk prediction using routine clinical data?

PloS one
BACKGROUND: Current approaches to predict cardiovascular risk fail to identify many people who would benefit from preventive treatment, while others receive unnecessary intervention. Machine-learning offers opportunity to improve accuracy by exploiti...

Ensemble Deep Learning for Biomedical Time Series Classification.

Computational intelligence and neuroscience
Ensemble learning has been proved to improve the generalization ability effectively in both theory and practice. In this paper, we briefly outline the current status of research on it first. Then, a new deep neural network-based ensemble method that ...

Development of Health Parameter Model for Risk Prediction of CVD Using SVM.

Computational and mathematical methods in medicine
Current methods of cardiovascular risk assessment are performed using health factors which are often based on the Framingham study. However, these methods have significant limitations due to their poor sensitivity and specificity. We have compared th...

Diet-induced weight loss and markers of endothelial dysfunction and inflammation in treated patients with type 2 diabetes.

Clinical nutrition ESPEN
BACKGROUND & AIMS: Overweight and obesity increase cardiovascular mortality in patients with type 2 diabetes (T2D). In a recent trial, however, diet-induced weight loss did not reduce the cardiovascular risk of patients with T2D, possibly due to the ...

A corpus of potentially contradictory research claims from cardiovascular research abstracts.

Journal of biomedical semantics
BACKGROUND: Research literature in biomedicine and related fields contains a huge number of claims, such as the effectiveness of treatments. These claims are not always consistent and may even contradict each other. Being able to identify contradicto...

Hybrid EANN-EA System for the Primary Estimation of Cardiometabolic Risk.

Journal of medical systems
The most important part of the early prevention of atherosclerosis and cardiovascular diseases is the estimation of the cardiometabolic risk (CMR). The CMR estimation can be divided into two phases. The first phase is called primary estimation of CMR...

Bayesian network modeling: A case study of an epidemiologic system analysis of cardiovascular risk.

Computer methods and programs in biomedicine
An extensive, in-depth study of cardiovascular risk factors (CVRF) seems to be of crucial importance in the research of cardiovascular disease (CVD) in order to prevent (or reduce) the chance of developing or dying from CVD. The main focus of data an...