Using Artificial Intelligence to Semi-Quantitate Coronary Calcium as an 'Incidentaloma' on Non-Gated, Non-Contrast CT Scans, A Single-Center Descriptive Study in West Michigan.
Connor Charles KerndtRajus ChopraPaul WeberAmy RechenbergDaniel SummersThomas BoydenDavid LangholzPublished in: Spartan medical research journal (2023)
Machine learning utilized in CT scans obtained for non-cardiac indications can detect and semi-quantitate CAC accurately. Artificial intelligence algorithms can accurately be applied to non-gated, non-contrast CT scans to identify CAC/ASCVD allowing for early medical intervention and improved clinical outcomes.
Keyphrases
- artificial intelligence
- machine learning
- contrast enhanced
- dual energy
- computed tomography
- big data
- deep learning
- magnetic resonance imaging
- image quality
- magnetic resonance
- positron emission tomography
- randomized controlled trial
- healthcare
- coronary artery disease
- coronary artery
- left ventricular
- atrial fibrillation