AIMC Topic: Heart Disease Risk Factors

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Automated Cardioailment Identification and Prevention by Hybrid Machine Learning Models.

Computational and mathematical methods in medicine Feb 15, 2022
Accurate prediction of cardiovascular disease is necessary and considered to be a difficult attempt to treat a patient effectively before a heart attack occurs. According to recent studies, heart disease is said to be one of the leading origins of de...
Heart Disease Risk Factors Humans Models, Cardiovascular Machine Learning Diagnosis, Computer-Assisted Algorithms Computational Biology Databases, Factual Bayes Theorem Female Heart Diseases Male Probability
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Machine learning-based diagnosis and risk factor analysis of cardiocerebrovascular disease based on KNHANES.

Scientific reports Feb 10, 2022
The prevalence of cardiocerebrovascular disease (CVD) is continuously increasing, and it is the leading cause of human death. Since it is difficult for physicians to screen thousands of people, high-accuracy and interpretable methods need to be prese...
Prevalence Nutrition Surveys Support Vector Machine Cerebrovascular Disorders Heart Disease Risk Factors Republic of Korea Female Risk Factors Male Cardiovascular Diseases Humans Machine Learning
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Deep learning segmentation and quantification method for assessing epicardial adipose tissue in CT calcium score scans.

Scientific reports Feb 10, 2022
Epicardial adipose tissue volume (EAT) has been linked to coronary artery disease and the risk of major adverse cardiac events. As manual quantification of EAT is time-consuming, requires specialized training, and is prone to human error, we develope...
Coronary Artery Disease Humans Calcium Tomography, X-Ray Computed Heart Disease Risk Factors Deep Learning Risk Adipose Tissue Pericardium Organ Size
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Application of ensemble machine learning algorithms on lifestyle factors and wearables for cardiovascular risk prediction.

Scientific reports Jan 20, 2022
This study looked at novel data sources for cardiovascular risk prediction including detailed lifestyle questionnaire and continuous blood pressure monitoring, using ensemble machine learning algorithms (MLAs). The reference conventional risk score c...
Humans Machine Learning Algorithms Exercise Surveys and Questionnaires Hypertension Singapore Coronary Artery Disease Female Aged Adult Male Middle Aged Calcium Heart Rate Heart Disease Risk Factors Life Style Blood Pressure Monitoring, Ambulatory
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Cardiovascular disease detection using machine learning and carotid/femoral arterial imaging frameworks in rheumatoid arthritis patients.

Rheumatology international Jan 11, 2022
The study proposes a novel machine learning (ML) paradigm for cardiovascular disease (CVD) detection in individuals at medium to high cardiovascular risk using data from a Greek cohort of 542 individuals with rheumatoid arthritis, or diabetes mellitu...
Male Cardiovascular Diseases Pilot Projects Arthritis, Rheumatoid Heart Disease Risk Factors Carotid Arteries Plaque, Atherosclerotic Femoral Artery Humans Machine Learning Female Reproducibility of Results Cross-Sectional Studies
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Score and Correlation Coefficient-Based Feature Selection for Predicting Heart Failure Diagnosis by Using Machine Learning Algorithms.

Computational and mathematical methods in medicine Dec 20, 2021
Cardiovascular disease (CVD) is one of the most common causes of death that kills approximately 17 million people annually. The main reasons behind CVD are myocardial infarction and the failure of the heart to pump blood normally. Doctors could diagn...
Chi-Square Distribution Databases, Factual Adult Electronic Health Records Male Female Middle Aged Humans Aged Diagnosis, Computer-Assisted Neural Networks, Computer Aged, 80 and over Computational Biology Machine Learning Logistic Models Algorithms Support Vector Machine Decision Trees Heart Failure Heart Disease Risk Factors
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Machine-Learning-Derived Model for the Stratification of Cardiovascular risk in Patients with Ischemic Stroke.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association Jul 31, 2021
UNLABELLED: Background Stratification of cardiovascular risk in patients with ischemic stroke is important as it may inform management strategies. We aimed to develop a machine-learning-derived prognostic model for the prediction of cardiovascular ri...
Predictive Value of Tests Ischemic Stroke Registries Heart Disease Risk Factors Male Cardiovascular Diseases Middle Aged Risk Assessment Time Factors Clinical Decision-Making Female Reproducibility of Results Aged Aged, 80 and over Humans Machine Learning Decision Support Techniques Prognosis Retrospective Studies
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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...
Female Aged Adult Male Middle Aged Humans Neural Networks, Computer Machine Learning Algorithms Kidney Failure, Chronic Heart Disease Risk Factors Aorta, Abdominal Vascular Calcification Renal Dialysis Computational Biology Logistic Models Support Vector Machine Fuzzy Logic
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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...
Logistic Models Area Under Curve ST Elevation Myocardial Infarction Percutaneous Coronary Intervention Hyperuricemia Heart Disease Risk Factors Humans Aged Male Middle Aged China Computational Biology Machine Learning Algorithms Prognosis Retrospective Studies Female
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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...
Humans Machine Learning Female Aged Coffee Proportional Hazards Models Coronary Disease Red Meat Protective Factors Incidence Stroke Heart Failure Heart Disease Risk Factors Milk Animals Male Cardiovascular Diseases Middle Aged Diet
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