Machine Learning Models for Automated Heart Disease Prognosis

Monkeypox: Considerations as a New Pandemic Looms

Ten Million Calls and Counting: Progress and Promise of Tobacco Quitlines in the U.S.

The goal of this American Heart Association Guide for Improving Cardiovascular Health at the Community Level (AHA Community Guide) is to provide a comprehensive inventory of evidence-based goals, strategies, and recommendations for cardiovascular disease (CVD) and stroke prevention that can be implemented on a community level. This guide advances the 2003 AHA Community Guide1 and the 2005 AHA statement on guidance for implementation2 by incorporating new evidence for community interventions gained over the past decade, expanding the target audience to include a broader range of community advocates, aligning with the concepts and terminology of the AHA 2020 Impact Goals, and recognizing the contributions of new public and private sector programs involving community interventions. In recent years, expanding arrays of programs and policies have been implemented in increasingly diverse communities to provide tools, strategies, and other best practices to potentially reduce the incidence of initial and recurrent cardiovascular events. The AHA Community Guide complements the AHA statement entitled “Population Approaches to Improve Diet, Physical Activity, and Smoking Habits”3 and supports the AHA 2020 goal4 to “improve the cardiovascular health of all Americans by 20%, while reducing deaths from CVDs and stroke by 20%.” The present AHA Community Guide supports the AHA 2020 goal by identifying exemplary regional or national programs that encourage cardiovascular health behaviors and health factors (formerly addressing risk behaviors and risk factors) from which communities might acquire proven strategies, expertise, and technical assistance for improving cardiovascular health. The AHA Community Guide seeks to prevent the onset of disease (primary prevention) and to maintain optimal cardiovascular health (primordial prevention) among broader segments of the population. Prior research indicates that using public health strategies such as sodium reduction in processed foods to lower blood pressure,5–8 tobacco laws to promote smoking cessation,9–11 and modification of …

Cardiology Patient Page. C-reactive protein: a simple test to help predict risk of heart attack and stroke.

Heart Disease and Stroke Statistics—2009 Update

Transfusion MedicineVolume 19, Issue 3 p. 149-151 The need for computerized tracking systems for resource-limited settings: the example of Georgetown, Guyana S. V. Basavaraju, Corresponding Author S. V. Basavaraju U.S. Centers for Disease Control and Prevention, National Center for HIV/AIDS, viral Hepatitis, STD, and TB Prevention, Division of Global AIDS, HIV Prevention Branch, Medical Transmission Team, Atlanta, GA, USASridhar V. Basavaraju, U.S. Centers for Disease Control and Prevention, Epidemic Intelligence Service, 1600 Clifton Road, NE, MS E-04, Atlanta, GA 30333, USA, Tel.: 404 639 6341; fax: 404 639 8114;e-mail:[email protected]Search for more papers by this authorJ. P. Pitman, J. P. Pitman U.S. Centers for Disease Control and Prevention, National Center for HIV/AIDS, viral Hepatitis, STD, and TB Prevention, Division of Global AIDS, HIV Prevention Branch, Medical Transmission Team, Atlanta, GA, USASearch for more papers by this authorN. Henry, N. Henry U.S. Centers for Disease Control and Prevention, Guyana,Search for more papers by this authorC. McEwan, C. McEwan Guyana National Blood Transfusion Service, GuyanaSearch for more papers by this authorC. Harry, C. Harry U.S. Centers for Disease Control and Prevention, Guyana,Search for more papers by this authorL. Hasbrouck, L. Hasbrouck U.S. Centers for Disease Control and Prevention, Guyana,Search for more papers by this authorL. Marum, L. Marum U.S. Centers for Disease Control and Prevention, National Center for HIV/AIDS, viral Hepatitis, STD, and TB Prevention, Division of Global AIDS, HIV Prevention Branch, Medical Transmission Team, Atlanta, GA, USASearch for more papers by this author S. V. Basavaraju, Corresponding Author S. V. Basavaraju U.S. Centers for Disease Control and Prevention, National Center for HIV/AIDS, viral Hepatitis, STD, and TB Prevention, Division of Global AIDS, HIV Prevention Branch, Medical Transmission Team, Atlanta, GA, USASridhar V. Basavaraju, U.S. Centers for Disease Control and Prevention, Epidemic Intelligence Service, 1600 Clifton Road, NE, MS E-04, Atlanta, GA 30333, USA, Tel.: 404 639 6341; fax: 404 639 8114;e-mail:[email protected]Search for more papers by this authorJ. P. Pitman, J. P. Pitman U.S. Centers for Disease Control and Prevention, National Center for HIV/AIDS, viral Hepatitis, STD, and TB Prevention, Division of Global AIDS, HIV Prevention Branch, Medical Transmission Team, Atlanta, GA, USASearch for more papers by this authorN. Henry, N. Henry U.S. Centers for Disease Control and Prevention, Guyana,Search for more papers by this authorC. McEwan, C. McEwan Guyana National Blood Transfusion Service, GuyanaSearch for more papers by this authorC. Harry, C. Harry U.S. Centers for Disease Control and Prevention, Guyana,Search for more papers by this authorL. Hasbrouck, L. Hasbrouck U.S. Centers for Disease Control and Prevention, Guyana,Search for more papers by this authorL. Marum, L. Marum U.S. Centers for Disease Control and Prevention, National Center for HIV/AIDS, viral Hepatitis, STD, and TB Prevention, Division of Global AIDS, HIV Prevention Branch, Medical Transmission Team, Atlanta, GA, USASearch for more papers by this author First published: 25 June 2009 https://doi.org/10.1111/j.1365-3148.2009.00925.xCitations: 1Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Citing Literature Volume19, Issue3June 2009Pages 149-151 RelatedInformation

Color lines: Disparities in pharmacy treatment, education, and practice

<title>Abstract</title> Behavioral and Anthropometric Determinants of Excessive Alcohol Consumption: Evidence from the BRFSS 2015 Introduction Excessive alcohol consumption is one of the leading preventable causes of morbidity and mortality in the adult population. Identifying behavioral and sociodemographic characteristics associated with this behavior can support the development of more effective prevention strategies. Methods Data were obtained from the 2015 Behavioral Risk Factor Surveillance System (BRFSS), a national survey coordinated by the Centers for Disease Control and Prevention (CDC) that collects self-reported health-related information from the adult population in the United States. The final sample included 253,680 individuals, with a mean body mass index (BMI) of 28.4. A binary logistic regression was performed to explore the association between excessive alcohol consumption (dependent variable) and the following predictors: fruit consumption, vegetable consumption, BMI, and sex. Odds ratios (ORs) and 95% confidence intervals (95% CI) were calculated. Results The model was globally significant (χ² = 1318, p &lt; 0.001), with a McFadden’s R² of 0.012. Fruit consumption was associated with a lower likelihood of excessive alcohol use (OR: 0.661; 95% CI: 0.638–0.684; p &lt; 0.001), whereas vegetable consumption was paradoxically associated with an increased risk (OR: 1.419; 95% CI: 1.352–1.489; p &lt; 0.001). Female sex (OR: 0.959; p &lt; 0.001) and higher BMI (OR: 0.959; p &lt; 0.001) were also protective factors. Conclusions The analysis of BRFSS 2015 data shows that specific dietary habits and individual characteristics, such as sex and body mass index, are significantly associated with excessive alcohol consumption. These findings may help guide future preventive strategies and educational interventions targeting at-risk groups.

Clinical Preventive Medicine in Primary Care: Background and Practice: 1. Rationale and Current Preventive Practices

Commentary

The Importance of Vaccinations

Aim: Coronary illness is one of the main sources of mortality in this current world. A basic test in the field of clinical information assessment is the expectation of cardiovascular infection. The fundamental target of this paper is to work on the exactness of the Data mining algorithms being used to improve heart disease prediction. We will be comparing the novel Random forest with K Nearest Neighbor to find out which of these can give us the best accuracy. Material and Methods: The study used 98 samples with Novel Random Forest and K Nearest Neighbor is executed with varying training and testing splits for predicting the accuracy for heart disease prediction with the 80% of G-power value and data about cardiovascular disease was gathered from numerous web sources, including latest research findings and threshold 0.05%, confidence interval 95% mean and standard deviation. The performance of the accuracy rate of the classifiers is examined using the heart disease dataset.. There was a statistical insignificant difference among Innovative Random Forest and K Nearest Neighbor p = 0.484 (p&gt;0.05). Results and Discussion: The accuracy of predicting heart disease in Novel Random Forest 90.16% and K Nearest Neighbor 67.21% is obtained. Conclusion: Prediction of Heart disease using the innovative Random Forest (RF) technique appears to be a significant improvement over the K Nearest Neighbor (KNN) algorithm in terms of accuracy.

Insurance is not a magic bullet for the multiple birth problem associated with assisted reproductive technology

Regulation of assisted reproductive technologies in the United States

The Risk of Homemade Infant Formulas: Historical and Contemporary Considerations