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Development of machine learning models for fractional flow reserve prediction in angiographically intermediate coronary lesions.

Marco LombardiRocco VergalloAndrea CostantinoFrancesco BianchiniTsunekazu KakutaTomasz PawlowskiAntonio Maria LeoneGennaro SardellaPierfrancesco AgostoniJonathan M HillGiovanni Luigi De MariaAdrian P BanningTomasz RolederAnouar BelkacemiCarlo TraniFrancesco Burzotta
Published in: Catheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions (2024)
ML algorithms derived from clinical, angiographic, and OCT parameters can identify patients with a positive or negative FFR.
Keyphrases
  • machine learning
  • artificial intelligence
  • coronary artery disease
  • coronary artery
  • big data
  • deep learning
  • optical coherence tomography
  • heart failure
  • atrial fibrillation