AIMC Topic: Heart Disease Risk Factors

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A Self-Representation-Based Fuzzy SVM Model for Predicting Vascular Calcification of Hemodialysis Patients.

Computational and mathematical methods in medicine Jul 27, 2021
In end-stage renal disease (ESRD), vascular calcification risk factors are essential for the survival of hemodialysis patients. To effectively assess the level of vascular calcification, the machine learning algorithm can be used to predict the vascu...
Fuzzy Logic Kidney Failure, Chronic Heart Disease Risk Factors Aorta, Abdominal Vascular Calcification Middle Aged Renal Dialysis Computational Biology Logistic Models Support Vector Machine Algorithms Female Aged Adult Male Humans Neural Networks, Computer Machine Learning
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Clinical Feature-Based Machine Learning Model for 1-Year Mortality Risk Prediction of ST-Segment Elevation Myocardial Infarction in Patients with Hyperuricemia: A Retrospective Study.

Computational and mathematical methods in medicine Jul 5, 2021
Accurate risk assessment of high-risk patients is essential in clinical practice. However, there is no practical method to predict or monitor the prognosis of patients with ST-segment elevation myocardial infarction (STEMI) complicated by hyperuricem...
Computational Biology Logistic Models Area Under Curve ST Elevation Myocardial Infarction Percutaneous Coronary Intervention Female Aged Male Middle Aged China Hyperuricemia Heart Disease Risk Factors Humans Machine Learning Algorithms Prognosis Retrospective Studies
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Association Between Coffee Intake and Incident Heart Failure Risk: A Machine Learning Analysis of the FHS, the ARIC Study, and the CHS.

Circulation. Heart failure Feb 9, 2021
BACKGROUND: Coronary heart disease, heart failure (HF), and stroke are complex diseases with multiple phenotypes. While many risk factors for these diseases are well known, investigation of as-yet unidentified risk factors may improve risk assessment...
Proportional Hazards Models Coronary Disease Red Meat Protective Factors Male Stroke Cardiovascular Diseases Humans Middle Aged Heart Failure Machine Learning Diet Heart Disease Risk Factors Female Incidence Milk Aged Coffee Animals
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Deep convolutional neural networks to predict cardiovascular risk from computed tomography.

Nature communications Jan 29, 2021
Coronary artery calcium is an accurate predictor of cardiovascular events. While it is visible on all computed tomography (CT) scans of the chest, this information is not routinely quantified as it requires expertise, time, and specialized equipment....
Female Reproducibility of Results Aged Male Cardiovascular Diseases Humans Retrospective Studies Tomography, X-Ray Computed Calcium Chest Pain Heart Disease Risk Factors Coronary Vessels Middle Aged Asymptomatic Diseases Risk Assessment Deep Learning Image Processing, Computer-Assisted Follow-Up Studies
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Multiclass machine learning vs. conventional calculators for stroke/CVD risk assessment using carotid plaque predictors with coronary angiography scores as gold standard: a 500 participants study.

The international journal of cardiovascular imaging Nov 12, 2020
Machine learning (ML)-based algorithms for cardiovascular disease (CVD) risk assessment have shown promise in clinical decisions. However, they usually predict binary events using only conventional risk factors. Our overall goal was to develop the "m...
Humans Machine Learning Decision Support Techniques Prognosis Female Coronary Angiography Reproducibility of Results Radiographic Image Interpretation, Computer-Assisted Diagnosis, Computer-Assisted Carotid Stenosis Aged Stroke Pilot Projects Cross-Sectional Studies Heart Disease Risk Factors Ultrasonography Coronary Stenosis Male Plaque, Atherosclerotic Support Vector Machine Middle Aged Predictive Value of Tests Risk Assessment
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Ischemia and outcome prediction by cardiac CT based machine learning.

The international journal of cardiovascular imaging Jul 4, 2020
Cardiac CT using non-enhanced coronary artery calcium scoring (CACS) and coronary CT angiography (cCTA) has been proven to provide excellent evaluation of coronary artery disease (CAD) combining anatomical and morphological assessment of CAD for card...
Prognosis Reproducibility of Results Risk Assessment Severity of Illness Index Predictive Value of Tests Humans Machine Learning Plaque, Atherosclerotic Vascular Calcification Computed Tomography Angiography Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Coronary Artery Disease Heart Disease Risk Factors Coronary Vessels
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From CT to artificial intelligence for complex assessment of plaque-associated risk.

The international journal of cardiovascular imaging Jul 2, 2020
The recent technological developments in the field of cardiac imaging have established coronary computed tomography angiography (CCTA) as a first-line diagnostic tool in patients with suspected coronary artery disease (CAD). CCTA offers robust inform...
Rupture, Spontaneous Plaque, Atherosclerotic Computed Tomography Angiography Coronary Stenosis Humans Coronary Angiography Machine Learning Radiographic Image Interpretation, Computer-Assisted Coronary Artery Disease Heart Disease Risk Factors Coronary Vessels Prognosis Reproducibility of Results Risk Assessment Severity of Illness Index Predictive Value of Tests
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Leisure time physical activity is associated with improved HDL functionality in high cardiovascular risk individuals: a cohort study.

European journal of preventive cardiology Jun 2, 2020
AIMS: Physical activity has consistently been shown to improve cardiovascular health and high-density lipoprotein-cholesterol levels. However, only small and heterogeneous studies have investigated the effect of exercise on high-density lipoprotein f...
Heart Disease Risk Factors Leisure Activities Cohort Studies Diabetes Mellitus, Type 2 Cholesterol Ester Transfer Proteins Cholesterol, HDL Humans Risk Factors Adult Cardiovascular Diseases Exercise
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State-of-the-Art Machine Learning Techniques Aiming to Improve Patient Outcomes Pertaining to the Cardiovascular System.

Journal of the American Heart Association Feb 13, 2020
Quality Indicators, Health Care Therapy, Computer-Assisted Outcome and Process Assessment, Health Care Humans Diagnosis, Computer-Assisted Machine Learning Treatment Outcome Precision Medicine Data Mining Cardiovascular Diseases Heart Disease Risk Factors Quality Improvement
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Development of a machine learning model for predicting cardiovascular risk factors and major adverse cardiovascular events in young adults with glucose metabolism disorders.

Medicina clinica Jun 13, 2025
BACKGROUND: Glucose metabolism disorders (GMDs) are a serious global public health issue, characterized by a high incidence rate and youthfulness. GMDs contribute to the occurrence of major adverse cardiovascular events (MACEs), meanwhile with the re...
Humans Male Cardiovascular Diseases Machine Learning Risk Assessment Female Heart Disease Risk Factors Risk Factors Glucose Metabolism Disorders Young Adult Adult
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