AIMC Topic: Cardiovascular Diseases

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Comparison of Machine Learning Approaches Toward Assessing the Risk of Developing Cardiovascular Disease as a Long-Term Diabetes Complication.

IEEE journal of biomedical and health informatics
The estimation of long-term diabetes complications risk is essential in the process of medical decision making. Guidelines for the management of Type 2 Diabetes Mellitus (T2DM) advocate calculating the Cardiovascular Disease (CVD) risk to initiate ap...

Ontology-based systematical representation and drug class effect analysis of package insert-reported adverse events associated with cardiovascular drugs used in China.

Scientific reports
With increased usage of cardiovascular drugs (CVDs) for treating cardiovascular diseases, it is important to analyze CVD-associated adverse events (AEs). In this study, we systematically collected package insert-reported AEs associated with CVDs used...

Prognostic Value of Combined Clinical and Myocardial Perfusion Imaging Data Using Machine Learning.

JACC. Cardiovascular imaging
OBJECTIVES: This study evaluated the added predictive value of combining clinical information and myocardial perfusion single-photon emission computed tomography (SPECT) imaging (MPI) data using machine learning (ML) to predict major adverse cardiac ...

ECG data compression using a neural network model based on multi-objective optimization.

PloS one
Electrocardiogram (ECG) data analysis is of great significance to the diagnosis of cardiovascular disease. ECG compression should be processed in real time, and the data should be based on lossless compression and have high predictability. In terms o...

Construction of environmental risk score beyond standard linear models using machine learning methods: application to metal mixtures, oxidative stress and cardiovascular disease in NHANES.

Environmental health : a global access science source
BACKGROUND: There is growing concern of health effects of exposure to pollutant mixtures. We initially proposed an Environmental Risk Score (ERS) as a summary measure to examine the risk of exposure to multi-pollutants in epidemiologic research consi...

Using Machine Learning to Define the Association between Cardiorespiratory Fitness and All-Cause Mortality (from the Henry Ford Exercise Testing Project).

The American journal of cardiology
Previous studies have demonstrated that cardiorespiratory fitness is a strong marker of cardiovascular health. Machine learning (ML) can enhance the prediction of outcomes through classification techniques that classify the data into predetermined ca...

The use of soft robotics in cardiovascular therapy.

Expert review of cardiovascular therapy
Robots have been employed in cardiovascular therapy as surgical tools and for automation of hospital systems. Soft robots are a new kind of robot made of soft deformable materials, that are uniquely suited for biomedical applications because they are...

Interaction between SELP genetic polymorphisms with inflammatory cytokine interleukin-6 (IL-6) gene variants on cardiovascular disease in Chinese Han population.

Mammalian genome : official journal of the International Mammalian Genome Society
The aim of the study is to investigate the impact of SELP and IL-6 genetic single-nucleotide polymorphisms (SNPs) and its gene-gene interaction on cardiovascular disease (CVD) risk based on Chinese population. A total of 1082 subjects (519 males, 563...

Developing a cardiovascular disease risk factor annotated corpus of Chinese electronic medical records.

BMC medical informatics and decision making
BACKGROUND: Cardiovascular disease (CVD) has become the leading cause of death in China, and most of the cases can be prevented by controlling risk factors. The goal of this study was to build a corpus of CVD risk factor annotations based on Chinese ...