AI Medical Compendium Topic:
Cardiovascular Diseases

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Machine Learning Model for Predicting CVD Risk on NHANES Data.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Cardiovascular disease (CVD) is a major health problem throughout the world. It is the leading cause of morbidity and mortality and also causes considerable economic burden to society. The early symptoms related to previous observations and abnormal ...

Segment Origin Prediction: A Self-supervised Learning Method for Electrocardiogram Arrhythmia Classification.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The automatic arrhythmia classification system has made a significant contribution to reducing the mortality rate of cardiovascular diseases. Although the current deep-learning-based models have achieved ideal effects in arrhythmia classification, th...

Performance of a Convolutional Neural Network and Explainability Technique for 12-Lead Electrocardiogram Interpretation.

JAMA cardiology
IMPORTANCE: Millions of clinicians rely daily on automated preliminary electrocardiogram (ECG) interpretation. Critical comparisons of machine learning-based automated analysis against clinically accepted standards of care are lacking.

Machine learning approaches improve risk stratification for secondary cardiovascular disease prevention in multiethnic patients.

Open heart
OBJECTIVES: Identifying high-risk patients is crucial for effective cardiovascular disease (CVD) prevention. It is not known whether electronic health record (EHR)-based machine-learning (ML) models can improve CVD risk stratification compared with a...