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An artificial intelligence difficulty scoring system for stone removal during ERCP: a prospective validation.

Li HuangYouming XuJie ChenFeng LiuDeqing WuWei ZhouLianlian WuTingting PangXu HuangKuo ZhangHong Gang Yu
Published in: Endoscopy (2022)
The CAD system effectively assessed and classified the degree of technical difficulty in endoscopic stone extraction during ERCP. In addition, it automatically provided a quantitative evaluation of CBD and stones, which in turn could help endoscopists to apply suitable procedures and interventional methods to minimize the possible risks associated with endoscopic stone removal.
Keyphrases
  • artificial intelligence
  • ultrasound guided
  • machine learning
  • big data
  • deep learning
  • editorial comment
  • coronary artery disease
  • high resolution
  • fluorescent probe
  • sensitive detection
  • mass spectrometry
  • quantum dots