AIMC Topic: Cardiovascular Diseases

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Cardiovascular disease detection: A hybrid machine learning-AI framework for personalized diagnosis and risk assessment.

PloS one
Cardiovascular disease (CVD) is considered the number one killer disease in the world, underlining the importance of the application of more accurate diagnostic and therapeutic tools. Traditional screening procedures usually do not provide identifica...

Using unsupervised machine learning methods to cluster cardio-metabolic profile of the middle-aged and elderly Chinese with general and central obesity.

BMC cardiovascular disorders
BACKGROUND: Obesity is a disease with high heterogeneity. Both overall obesity and central obesity are associated with increased risks of having cardio-metabolic co-morbidities. This study is aimed to examine the cardio-metabolic characteristics and ...

Long-term exposure to ambient air pollution and cardiometabolic multimorbidity in Chinese adults over 45 years.

Scientific reports
The rising prevalence of cardiometabolic multimorbidity (CMM), characterized by the coexistence of two or more cardiometabolic disorders, poses a significant public health challenge in aging populations. While ambient air pollution is a recognized en...

Cardiovascular risk prediction in diabetes: a hybrid machine learning approach.

Biomedical physics & engineering express
Cardiovascular disease (CVD) is a major cause of morbidity and mortality in diabetic populations. Early detection of cardiovascular risk in diabetes is crucial to reduce complications, particularly in resource-limited settings. This study aimed to de...

A Crossroads in Cardiovascular Medicine: Progress and Barriers to Impact.

Circulation
During the past 75 years, advances in cardiovascular science and technology have significantly reduced morbidity and mortality. In 2012, Drs Nabel and Braunwald reviewed this progress in , highlighting the landmark innovations that contributed to the...

Cardiovascular risk assessment enhanced by automated machine learning in a multi-phase study.

Scientific reports
Cardiovascular diseases (CVDs) are the leading cause of death worldwide, and current predictors such as lipoprotein (a) [Lp(a)] and risk scores have limitations. Automated machine learning (AutoML) offers the potential to improve CVD risk prediction ...

Applying spectral analysis to the arterial pulse to discriminate cardiovascular side effects following administration of Moderna's mRNA-1273 vaccine.

European journal of pharmacology
Vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have demonstrated strong efficacy in preventing symptomatic disease, but adverse cardiovascular side effects have been reported. This study investigated whether noninvasive...

Machine learning-based integration of pericoronary adipose tissue and clinical risk factors for cardiovascular risk prediction in type 2 diabetes: a retrospective cohort study.

European journal of medical research
BACKGROUND: Cardiovascular disease remains the predominant cause of morbidity and mortality in individuals with type 2 diabetes mellitus (T2DM). Traditional risk models are limited in predictive accuracy. Pericoronary adipose tissue (PCAT), a novel i...