Using machine learning algorithms to review computed tomography scans and assess risk for cardiovascular disease: Retrospective analysis from the National Lung Screening Trial (NLST).
Amos StemmerRan ShadmiEldad ElnekaveDavid ChettritDenitza P BlagevMila OrlovskyLisa DeutschEldad ElnekavePublished in: PloS one (2020)
The three automated machine learning algorithms could help physicians to assess the incidence and risk of CVD mortality in this specific population. Application of these algorithms to existing LDCT scans can provide valuable health care information and assist in future research.
Keyphrases
- machine learning
- computed tomography
- cardiovascular disease
- artificial intelligence
- deep learning
- healthcare
- big data
- positron emission tomography
- risk factors
- primary care
- contrast enhanced
- dual energy
- cardiovascular events
- magnetic resonance imaging
- clinical trial
- type diabetes
- study protocol
- quality improvement
- phase iii
- randomized controlled trial
- phase ii
- image quality
- current status
- coronary artery disease
- open label
- single cell