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Predicting lymph node metastasis from primary tumor histology and clinicopathologic factors in colorectal cancer using deep learning.

Justin D KrogueShekoofeh AziziFraser TanIsabelle Flament-AuvigneTrissia BrownMarkus PlassRobert ReihsHeimo MüllerKurt ZatloukalPema RichesonGreg S CorradoLily H PengCraig H MermelYuan LiuPo-Hsuan Cameron ChenSaurabh GombarThomas MontineJeanne ShenDavid F SteinerEllery Wulczyn
Published in: Communications medicine (2023)
This work demonstrates an effective approach to combine deep learning with established clinicopathologic factors in order to identify independently informative features associated with LNM. Further work building on these specific results may have important impact in prognostication and therapeutic decision making for LNM. Additionally, this general computational approach may prove useful in other contexts.
Keyphrases
  • deep learning
  • lymph node metastasis
  • decision making
  • squamous cell carcinoma
  • artificial intelligence
  • convolutional neural network
  • papillary thyroid
  • machine learning