AIMC Topic: Cardiovascular Diseases

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Classification of Cardiovascular Disease via A New SoftMax Model.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
Cardiovascular disease clinical diagnosis is an essentially problem of pattern recognition. In the traditional intelligent diagnosis, the evaluation of classification algorithm is based on the final accuracy of the disease diagnosis. In this paper, a...
Cluster Analysis Regression Analysis Humans Neural Networks, Computer Algorithms Cardiovascular Diseases
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Teaching cardiovascular medicine to machines.

Cardiovascular research Jul 1, 2018
Humans Ventricular Remodeling Hemodynamics Machine Learning Diagnosis, Computer-Assisted Prognosis Models, Cardiovascular Therapy, Computer-Assisted Diffusion of Innovation Cardiovascular Diseases Patient-Specific Modeling
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Cardiorenal Outcomes in the CANVAS, DECLARE-TIMI 58, and EMPA-REG OUTCOME Trials: A Systematic Review.

Reviews in cardiovascular medicine Jun 30, 2018
In this systematic review, we sought to summarize the 3 recent sodium-glucose cotransporter 2 inhibitor (SGLT2i) trials (Dapagliflozin Effect on CardiovasculAR Events (DECLARE-TIMI 58), Canagliflozin Cardiovascular Assessment Study (CANVAS) Program, ...
Sodium-Glucose Transporter 2 Inhibitors Blood Glucose Glucosides Sodium-Glucose Transporter 2 Randomized Controlled Trials as Topic Diabetes Mellitus, Type 2 Risk Factors Humans Benzhydryl Compounds Cause of Death Cardiovascular Diseases Treatment Outcome Research Design Health Status Canagliflozin Comorbidity Biomarkers Kidney Diseases
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Artificial Intelligence in Cardiology.

Journal of the American College of Cardiology Jun 12, 2018
Artificial intelligence and machine learning are poised to influence nearly every aspect of the human condition, and cardiology is not an exception to this trend. This paper provides a guide for clinicians on relevant aspects of artificial intelligen...
Humans Artificial Intelligence Machine Learning Algorithms Cardiovascular Diseases Cardiology
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What's in Store for Cardiovascular Ultrasound in the Future.

Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography May 1, 2018
Humans Machine Learning Cardiovascular Diseases Societies, Medical Echocardiography Virtual Reality Cardiology
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Eyeing cardiovascular risk factors.

Nature biomedical engineering Mar 1, 2018
Image Interpretation, Computer-Assisted Cardiovascular Diseases Deep Learning Retina Algorithms Risk Factors Humans
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All eyes are on AI.

Nature biomedical engineering Mar 1, 2018
Humans Image Interpretation, Computer-Assisted Algorithms Artificial Intelligence Cardiovascular Diseases Retinal Diseases Retina
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Learning to think like Machines.

Indian heart journal Jan 1, 2018
Prevalence India Diagnostic Techniques, Cardiovascular Humans Cardiovascular Diseases Machine Learning Risk Assessment Algorithms
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The dose-response association between estimated glomerular filtration rate and prognosis of patients with ST-segment elevation myocardial infarction from rural areas of China's Liaoning province.

Medicine Dec 1, 2017
We aimed to investigate the dose-response associations between chronic kidney disease (CKD), and short and long-term cardiovascular outcomes, to characterize these associations by drawing dose-response curves based on a Chinese rural ST-segment eleva...
Middle Aged Comorbidity Severity of Illness Index Logistic Models Membrane Proteins China Hospital Mortality Aged, 80 and over Adult Male Humans Cardiovascular Diseases Biomarkers Prognosis Female Aged Proportional Hazards Models Rural Population Hyperlipidemias Age Factors Renal Insufficiency, Chronic Drosophila Proteins ST Elevation Myocardial Infarction Glomerular Filtration Rate
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Visualization of Cancer and Cardiovascular Disease Co-Occurrence With Network Methods.

JCO clinical cancer informatics Nov 1, 2017
PURPOSE: Cancer and cardiovascular disease (CVD) are common causes of morbidity and mortality, and measurement and interpretation of their co-occurrence rate have important implications for public health and patient care. Here, we present the raw and...
Population Surveillance United Kingdom Odds Ratio Life Style Risk Assessment Humans Neoplasms Neural Networks, Computer Comorbidity Male Aged Cardiovascular Diseases Adult Middle Aged Female Risk Factors
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