AIMC Topic: Heart Disease Risk Factors
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Prediction of cardiovascular risk factors from retinal fundus photographs: Validation of a deep learning algorithm in a prospective non-interventional study in Kenya.
Diabetes, obesity & metabolism
Apr 15, 2024
AIM: Hypertension and diabetes mellitus (DM) are major causes of morbidity and mortality, with growing burdens in low-income countries where they are underdiagnosed and undertreated. Advances in machine learning may provide opportunities to enhance d...
Advanced cardiac imaging, machine learning, and heart age for cardiovascular risk stratification.
The international journal of cardiovascular imaging
Apr 13, 2024
Deep Learning to Estimate Cardiovascular Risk From Chest Radiographs : A Risk Prediction Study.
Annals of internal medicine
Mar 26, 2024
BACKGROUND: Guidelines for primary prevention of atherosclerotic cardiovascular disease (ASCVD) recommend a risk calculator (ASCVD risk score) to estimate 10-year risk for major adverse cardiovascular events (MACE). Because the necessary inputs are o...
Artificial intelligence in preventive cardiology.
Progress in cardiovascular diseases
Mar 7, 2024
Artificial intelligence (AI) is a field of study that strives to replicate aspects of human intelligence into machines. Preventive cardiology, a subspeciality of cardiovascular (CV) medicine, aims to target and mitigate known risk factors for CV dise...
Artificial intelligence in the risk prediction models of cardiovascular disease and development of an independent validation screening tool: a systematic review.
BMC medicine
Feb 5, 2024
BACKGROUND: A comprehensive overview of artificial intelligence (AI) for cardiovascular disease (CVD) prediction and a screening tool of AI models (AI-Ms) for independent external validation are lacking. This systematic review aims to identify, descr...
Heart disease risk factors detection from electronic health records using advanced NLP and deep learning techniques.
Scientific reports
May 3, 2023
Heart disease remains the major cause of death, despite recent improvements in prediction and prevention. Risk factor identification is the main step in diagnosing and preventing heart disease. Automatically detecting risk factors for heart disease i...
Can deep learning on retinal images augment known risk factors for cardiovascular disease prediction in diabetes? A prospective cohort study from the national screening programme in Scotland.
International journal of medical informatics
Apr 18, 2023
AIMS: This study's objective was to evaluate whether deep learning (DL) on retinal photographs from a diabetic retinopathy screening programme improve prediction of incident cardiovascular disease (CVD).
Artificial intelligence and body composition.
Diabetes & metabolic syndrome
Feb 26, 2023
AIMS: Although obesity is associated with chronic disease, a large section of the population with high BMI does not have an increased risk of metabolic disease. Increased visceral adiposity and sarcopenia are also risk factors for metabolic disease i...
Deep-Learning for Epicardial Adipose Tissue Assessment With Computed Tomography: Implications for Cardiovascular Risk Prediction.
JACC. Cardiovascular imaging
Feb 8, 2023
BACKGROUND: Epicardial adipose tissue (EAT) volume is a marker of visceral obesity that can be measured in coronary computed tomography angiograms (CCTA). The clinical value of integrating this measurement in routine CCTA interpretation has not been ...
Epidemiological predictive modeling: lessons learned from the Kuopio ischemic heart disease risk factor study.
Annals of epidemiology
Mar 27, 2022
PURPOSE: The use of predictive models in epidemiology is relatively narrow as most of the studies report results of traditional statistical models such as Linear, Logistic, or Cox regressions. In this study, a high-dimensional epidemiological cohort,...
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