AIMC Topic: Cardiovascular Diseases

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Sarcopenia prediction model based on machine learning and SHAP values for community-based older adults with cardiovascular disease in China.

Frontiers in public health
BACKGROUND: Sarcopenia (SP), is recognized as a complication of cardiovascular disease (CVD), but few relevant diagnostic models have been developed. This study aims to establish an interpretable diagnostic model for the occurrence of SP in older adu...

The use of artificial intelligence to identify ophthalmic biomarkers in cardiovascular disease and stroke: a narrative review.

Sao Paulo medical journal = Revista paulista de medicina
BACKGROUND: Cardiovascular disease (CVD) and stroke are among the leading causes of death worldwide.

Enhancing Patient Education on Cardiovascular Rehabilitation with Large Language Models.

Missouri medicine
INTRODUCTION: There are barriers that exist for individuals to adhere to cardiovascular rehabilitation programs. A key driver to patient adherence is appropriately educating patients. A growing education tool is using large language models to answer ...

Determinants of developing cardiovascular disease risk with emphasis on type-2 diabetes and predictive modeling utilizing machine learning algorithms.

Medicine
This research aims to enhance our comprehensive understanding of the influence of type-2 diabetes on the development of cardiovascular diseases (CVD) risk, its underlying determinants, and to construct precise predictive models capable of accurately ...

Artificial Intelligence in Cardiovascular Clinical Trials.

Journal of the American College of Cardiology
Randomized clinical trials are the gold standard for establishing the efficacy and safety of cardiovascular therapies. However, current pivotal trials are expensive, lengthy, and insufficiently diverse. Emerging artificial intelligence (AI) technolog...

Artificial intelligence-enabled electrocardiogram for mortality and cardiovascular risk estimation: a model development and validation study.

The Lancet. Digital health
BACKGROUND: Artificial intelligence (AI)-enabled electrocardiography (ECG) can be used to predict risk of future disease and mortality but has not yet been adopted into clinical practice. Existing model predictions do not have actionability at an ind...

Tailoring Risk Prediction Models to Local Populations.

JAMA cardiology
IMPORTANCE: Risk estimation is an integral part of cardiovascular care. Local recalibration of guideline-recommended models could address the limitations of existing tools.