Heart disease remains a leading cause of mortality worldwide, prompting healthcare researchers to leverage analytical tools for comprehensive data analysis. This study focuses on exploring crucial parameters and employing deep learning (DL) techniques to enhance understanding a...
Cardiovascular heart disease prediction using machine learning classifiers with data mining techniques Turkish Online Journal of Qualitative InquiryShareefunnisa, SyedMahima, Devarapalli RetzPadma, Y.
While RF, XGBoost and DNN have demonstrated high-prediction accuracy than simpler models such as DT in prior studies, they are also regarded as ‘black-box’ models since it is difficult for humans to comprehend their behavior in predicting the outcome. Interpretability of the ML model is the ...
A multi-ancestry polygenic risk score improves risk prediction for coronary artery disease A polygenic risk score for coronary artery disease developed using data from individuals of five different ancestries has increased accuracy across diverse populations. ...
To provide an overview of prediction models for risk of cardiovascular disease (CVD) in the general population.聽Systematic review.聽Medline and Embase until June 2013.聽Studies describing the development or external validation of a multivariable model for predicting CVD risk in the general population...
Coordinated Care for Optimization of Cardiovascular Preventive Therapies in Patients With Diabetes Nin-Chieh Hsu, MD, PhD; Yin-Chih Fu, MD, PhD; Chia-Hao Hsu, MD JAMA Original Investigation Addition of Urinary Albumin Excretion to Standard Biomarkers for Cardiovascular Disease Risk Prediction Benjamin...
Multimodal AI/ML for discovering novel biomarkers and predicting disease using multi-omics profiles of patients with cardiovascular diseases Article Open access 03 November 2024 Disease prediction with multi-omics and biomarkers empowers case–control genetic discoveries in the UK Biobank Article Open...
Cardiovascular disease DL: Deep learning ECG: Electrocardiography EHR: Electronic health record FDA: U.S. Food and Drug Administration ML: Machine learning NHANES: National Health and Nutrition Examination Survey RCT: Randomized controlled trials
BACKGROUND: The accurate assessment of individual risk can be of great value to guiding and facilitating the prevention of atherosclerotic cardiovascular disease (ASCVD). However, prediction models in common use were formulated primarily in white populations. The China-PAR project (Prediction for ASCVD...
The Pooled Cohort Equations (PCEs) are race- and sex-specific Cox proportional hazards (PH)-based models used for 10-year atherosclerotic cardiovascular disease (ASCVD) risk prediction with acceptable discrimination. In recent years, neural network models have gained increasing popularity with their ...