Real-Time Artificial Intelligence-Based Guidance of Echocardiographic Imaging by Novices: Image Quality and Suitability for Diagnostic Interpretation and Quantitative Analysis.
Victor Mor-AviBijoy KhandheriaRobert KlempfnerJuan I CotellaMerav MorenoDenise IgnatowskiBrittney GuileHailee J HayesKyle HipkeAbigail E KaminskiDan SpiegelsteinNoa AvisarItay KezurerAsaf MazurskyRan HandelYotam PelegShir AvrahamAchiau LudomirskyRoberto M LangPublished in: Circulation. Cardiovascular imaging (2023)
After minimal training with the real-time guidance software, novice users can acquire images of diagnostic quality approaching that of expert sonographers in most patients. This technology may increase adoption and improve accuracy of point-of-care cardiac ultrasound.
Keyphrases
- artificial intelligence
- image quality
- deep learning
- ejection fraction
- end stage renal disease
- machine learning
- big data
- left ventricular
- chronic kidney disease
- newly diagnosed
- computed tomography
- magnetic resonance imaging
- high resolution
- peritoneal dialysis
- pulmonary hypertension
- electronic health record
- heart failure
- mitral valve
- convolutional neural network
- quality improvement
- atrial fibrillation
- left atrial
- magnetic resonance
- ultrasound guided
- virtual reality
- contrast enhanced
- contrast enhanced ultrasound