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

Validation of a Derived International Patient Severity Phenotype to Support COVID-19 Analytics from Electronic Health Record Data

Klann, Jeffrey G, Griffin M Weber, Hossein Estiri, Bertrand Moal, Paul Avillach, Chuan Hong, Victor M Castro, et al. 2020. “Validation of a Derived International Patient Severity Phenotype to Support COVID-19 Analytics from Electronic Health Record Data.”
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