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Validating an algorithm to identify metastatic gastric cancer in the absence of routinely collected TNM staging data.

Alyson L MaharYunni JeongBrandon ZagorskiNatalie Coburn
Published in: BMC health services research (2018)
Algorithms identifying metastatic gastric cancer can be used for research purposes using administrative healthcare data, although they are imperfect measures. The properties of these algorithms may be generalizable to other high fatality cancers and other healthcare systems. This study provides further support for the collection of population-based, TNM stage data.
Keyphrases
  • healthcare
  • machine learning
  • electronic health record
  • big data
  • squamous cell carcinoma
  • deep learning
  • small cell lung cancer
  • artificial intelligence
  • data analysis
  • health information
  • young adults