Machine learning

Showing 9 of 0 results

• Japanese language EHR LLM extraction of longitudinal unstructured ECOG performance status

  JSMO Annual Meeting

  • Publication summary
  • Publications
  • Machine learning
  • Artificial intelligence
• Ensuring reliability of curated EHR-derived data: The Validation of Accuracy for LLM/ML-Extracted Information and Data (VALID) Framework

  JCO Cancer Clinical Informatics

  • Publication summary
  • Publications
  • Machine learning
  • Quality improvement
  • Quality reporting
• Flatiron Health announces research to be presented at the 2025 European Society For Medical Oncology AI & Digital Oncology Congress
  • Machine learning
  • Press releases
• A pan-tumor and pan-country approach to LLM-based extraction of systemic therapies from the electronic health record

  ESMO AI & Digital Oncology

  • Publication summary
  • Publications
  • Machine learning
  • Tumor agnostic
  • Data management
• A framework for evaluating performance of LLM-based extraction from the electronic health record across different healthcare systems

  ESMO AI & Digital Oncology

  • Publication summary
  • Publications
  • Machine learning
  • Quality improvement
  • Data management
• Privacy-preserving error analysis loop For ML-based extraction of oncology EHR data

  ESMO AI & Digital Oncology

  • Publication summary
  • Publications
  • Data science
  • Machine learning
  • Data management
• Structuring GDPR-compliant private networks to enable LLM-Extracted oncology data on pseudonymized patient EHR data in Europe

  ESMO AI & Digital Oncology

  • Publication summary
  • Publications
  • Data science
  • Machine learning
• Survival prediction in advanced NSCLC (aNSCLC) amid evolving standards of care (SOC): Digital twin modeling incorporating LLM-extracted clinical context

  ESMO AI & Digital Oncology

  • Publication summary
  • Publications
  • Machine learning
• Behind the Research: An Exploration of Real-World Data's Ability to Support Adverse Event Surveillance at ISPOR Europe
  • Real-world evidence
  • Machine learning
  • Breast cancer
  • Regulatory
  • Post marketing requirements