Epidemiological aspects of heart diseases

Shi, Aimin; Tao, Ziqi; Peng, Wei; Zhao, Jing

doi:10.3892/etm.2016.3541

Cited by 53 publications

(34 citation statements)

References 53 publications

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“…Although sex differences in CVDs are caused in part by environmental or social differences between men and women (e.g., occupational hazards, habits, social stresses), 5–7 we focus here on biological factors that are important and tractable for study in animal models.…”

Section: Conceptual Frameworkmentioning

confidence: 99%

Sex Hormones and Sex Chromosomes Cause Sex Differences in the Development of Cardiovascular Diseases

Arnold

Cassis

Eghbali

et al. 2017

ATVB

254

176

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This review summarizes recent evidence concerning hormonal and sex chromosome effects in obesity, atherosclerosis, aneurysms, ischemia/reperfusion injury, and hypertension. Cardiovascular diseases (CVD) occur and progress differently in the two sexes, because biological factors differing between the sexes have sex-specific protective and harmful effects. By comparing the two sexes directly, and breaking down sex into its component parts, one can discover sex-biasing protective mechanisms that might be targeted in the clinic. Gonadal hormones, especially estrogens and androgens, have long been found to account for some sex differences in CVD, and molecular mechanisms mediating these effects have recently been elucidated. More recently the inherent sexual inequalities in effects of sex chromosome genes have also been implicated as contributors in animal models of CVDs, especially a deleterious effect of the second X chromosome found in females but not in males. Hormonal and sex chromosome mechanisms interact in the sex-specific control of certain diseases, sometimes by opposing the action of the other.

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Section: Conceptual Frameworkmentioning

confidence: 99%

Sex Hormones and Sex Chromosomes Cause Sex Differences in the Development of Cardiovascular Diseases

Arnold

Cassis

Eghbali

et al. 2017

ATVB

254

176

View full text Add to dashboard Cite

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“…Cardiovascular diseases are one of the leading causes of death worldwide, causing around a third of deaths every year. Out of all cardiovascular diseases, coronary artery disease is the cause of most deaths [1] [2]. As such, there is great interest in diagnosing, treating and preventing this disease.…”

Section: Introductionmentioning

confidence: 99%

Machine Learning Classifications of Coronary Artery Disease

Nassif

Mahdi

Nasir

et al. 2018

2018 International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP)

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Coronary Artery Disease (CAD) is one of the leading causes of death worldwide, and so it is very important to correctly diagnose patients with the disease. For medical diagnosis, machine learning is a useful tool; however features and algorithms must be carefully selected to get accurate classification. To this effect, three feature selection methods have been used on 13 input features from the Cleveland dataset with 297 entries, and 7 were selected. The selected features were used to train three different classifiers, which are SVM, Naïve Bayes and KNN using 10-fold cross-validation. The resulting models evaluated using Accuracy, Recall, Specificity and Precision. It is found that the Naïve Bayes classifier performs the best on this dataset and features, outperforming or matching SVM and KNN in all the four evaluation parameters used and achieving an accuracy of 84%.

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“…According to the available research, coronary heart disease (CHD) ranks first among the causes of mortality in the world. In Ukraine, about 350 thousand people annually die of CHD [1]. The main pathogenetic cause of CHD is atherosclerosis (AS) of vessels, which is accompanied by disruption of lipid metabolism.…”

mentioning

confidence: 99%