Prediction models for cardiovascular disease risk in the general population: systematic review
Objective To provide an overview of prediction models for risk of cardiovascular disease
(CVD) in the general population. Design Systematic review. Data sources Medline and …
(CVD) in the general population. Design Systematic review. Data sources Medline and …
The role of aspirin in the prevention of cardiovascular disease
SV Ittaman, JJ VanWormer… - Clinical medicine & …, 2014 - Marshfield Clinic
Aspirin therapy is well-accepted as an agent for the secondary prevention of cardiovascular
events and current guidelines also define a role for aspirin in primary prevention. In this …
events and current guidelines also define a role for aspirin in primary prevention. In this …
A novel risk score to predict cardiovascular disease risk in national populations (Globorisk): a pooled analysis of prospective cohorts and health examination surveys
Background Treatment of cardiovascular risk factors based on disease risk depends on valid
risk prediction equations. We aimed to develop, and apply in example countries, a risk …
risk prediction equations. We aimed to develop, and apply in example countries, a risk …
Laboratory-based and office-based risk scores and charts to predict 10-year risk of cardiovascular disease in 182 countries: a pooled analysis of prospective cohorts …
Background Worldwide implementation of risk-based cardiovascular disease (CVD)
prevention requires risk prediction tools that are contemporarily recalibrated for the target …
prevention requires risk prediction tools that are contemporarily recalibrated for the target …
[HTML][HTML] Adapting machine learning techniques to censored time-to-event health record data: A general-purpose approach using inverse probability of censoring …
Abstract Models for predicting the probability of experiencing various health outcomes or
adverse events over a certain time frame (eg, having a heart attack in the next 5 years) …
adverse events over a certain time frame (eg, having a heart attack in the next 5 years) …
A regularized deep learning approach for clinical risk prediction of acute coronary syndrome using electronic health records
Objective: Acute coronary syndrome (ACS), as a common and severe cardiovascular
disease, is a leading cause of death and the principal cause of serious long-term disability …
disease, is a leading cause of death and the principal cause of serious long-term disability …
Comparison of machine learning approaches toward assessing the risk of develo** cardiovascular disease as a long-term diabetes complication
The estimation of long-term diabetes complications risk is essential in the process of medical
decision making. Guidelines for the management of Type 2 Diabetes Mellitus (T2DM) …
decision making. Guidelines for the management of Type 2 Diabetes Mellitus (T2DM) …
Screening for coronary heart disease with electrocardiography: US Preventive Services Task Force recommendation statement
VA Moyer… - Annals of internal …, 2012 - acpjournals.org
Chinese translation Description: Update of the 2004 US Preventive Services Task Force
(USPSTF) recommendation statement on screening for coronary heart disease (CHD) …
(USPSTF) recommendation statement on screening for coronary heart disease (CHD) …
Preventive care recommendations to promote health equity
Background: Avoidable disparities in health outcomes persist in Canada despite substantial
investments in a publicly funded health care system that includes preventive services. Our …
investments in a publicly funded health care system that includes preventive services. Our …
Data mining for censored time-to-event data: a Bayesian network model for predicting cardiovascular risk from electronic health record data
Abstract Models for predicting the risk of cardiovascular (CV) events based on individual
patient characteristics are important tools for managing patient care. Most current and …
patient characteristics are important tools for managing patient care. Most current and …