Skip to main content
Surgical Informatics Lab
Primary menu
  • Research
  • People
  • Publications
  • Webinars
  • Resources
  • Open Positions

Validation of an internationally derived patient severity phenotype to support COVID-19 analytics from electronic health record data

Klann, Jeffrey G, Hossein Estiri, Griffin M Weber, Bertrand Moal, Paul Avillach, Chuan Hong, Amelia LM Tan, et al. 2021. “Validation of an Internationally Derived Patient Severity Phenotype to Support COVID-19 Analytics from Electronic Health Record Data”. Journal of the American Medical Informatics Association 28 (7): 1411-20.
Last updated on 02/21/2025

Recent Publications

  • Is More Thinking Always Better? First Impressions of ChatGPT-5 in Surgery Conversations
  • Development of a Claims-Based Computable Phenotype for Ulcerative Colitis Flares
  • Evaluating Capabilities of Large Language Models: Performance of GPT4 on Surgical Knowledge Assessments
  • Implications of mappings between International Classification of Diseases clinical diagnosis codes and Human Phenotype Ontology terms
  • Response to: Comment on “Integrating Human Intuition into Prediction Algorithms for Improved Surgical Risk Stratification”
  • Implications of mappings between ICD clinical diagnosis codes and Human Phenotype Ontology terms
  • Twitter
Powered byOpenScholar®Admin Login