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 variability
- heavy metals
- heart rate
- tertiary care
- cardiovascular events
- oxidative stress
- type diabetes
- mental health
- climate change
- metabolic syndrome
- cardiovascular risk factors
- clinical evaluation