Cardiovascular disease mortality is increasing in North Carolina with persistent inequality by race, income, and location. Artificial intelligence (AI) can repurpose the widely available electrocardiogram (ECG) for enhanced assessment of cardiac dysfunction. By identifying accelerated cardiac aging from the ECG, AI offers novel insights into risk assessment and prevention.
Keyphrases
- artificial intelligence
- risk assessment
- machine learning
- cardiovascular disease
- big data
- deep learning
- human health
- left ventricular
- heart rate
- heart rate variability
- heavy metals
- tertiary care
- cardiovascular events
- oxidative stress
- physical activity
- mental health
- risk factors
- metabolic syndrome
- blood pressure
- cardiovascular risk factors
- climate change
- coronary artery disease