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Design and Evaluation of a Computational Phenotype to Identify Patients With Metastatic Breast Cancer Within the Electronic Health Record.

Benjamin NeelyMohammad ShahsahebiCaitlin E MarksSteve PowerAndrew S KanterClaire HowellTerry HyslopJennifer K Plichta
Published in: JCO clinical cancer informatics (2022)
Hospital systems with robust EHRs and reliable mapping to SNOMED have the ability to use standard codes to derive computational phenotypes. These algorithms perform reasonably well and have the added ability to be run at disparate health care facilities. Better tooling to navigate the polyhierarchical structure of SNOMED ontology could yield better-performing computational phenotypes.
Keyphrases
  • electronic health record
  • metastatic breast cancer
  • healthcare
  • adverse drug
  • clinical decision support
  • machine learning
  • high resolution
  • deep learning
  • acute care
  • high density
  • emergency department
  • mass spectrometry