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Conditional inference tree models to perceive depth of invasion in T1 colorectal cancer.

Hiroyuki TakamaruMatthew StammersFumito YanagisawaYasuhiko MizuguchiMasau SekiguchiMasayoshi YamadaTaku SakamotoTakahisa MatsudaYutaka Saito
Published in: Surgical endoscopy (2022)
We discovered that machine-learning classifiers, including JNET and macroscopic features, provide the best non-invasive screen to exclude deeper invasion for suspected Tis/T1 lesions. Adding this algorithm improves depth diagnosis of T1 colorectal lesions for both expert and non-expert endoscopists.
Keyphrases
  • machine learning
  • cell migration
  • optical coherence tomography
  • clinical practice
  • deep learning
  • artificial intelligence
  • high throughput
  • pulmonary embolism
  • big data
  • single cell