Machine learning

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• A geyser of biomarkers: Extracting data from NGS reports
  • Flatiron stories
  • Machine learning
• Concordance of response-based clinical trial and machine learning–generated real-world end points

  ASCO Annual Meeting

  • Publication summary
  • Publications
  • Machine learning
  • Non-small cell lung cancer
• Leveraging machine learning to assess the association of rash and survival in patients with advanced NSCLC

  ISPOR

  • Real-world evidence
  • Publication summary
  • Publications
  • Machine learning
• Performance assessment and validation of real-world response data generated using a deep learning-based natural language processing model across multiple solid tumors

  ISPOR

  • Real-world evidence
  • Publication summary
  • Publications
  • Machine learning
• Advancing breast cancer research in Japan using EHR-derived real-world data

  ISPOR

  • Real-world evidence
  • Publication summary
  • Publications
  • Machine learning
• Patient characteristics and treatment patterns in extensive-stage small cell lung cancer (ES-SCLC)

  ISPOR

  • Publication summary
  • Publications
  • Machine learning
  • Small cell lung cancer
• Using large language models to extract PD-L1 biomarker data from electronic health records

  AI in Precision Oncology

  • Publication summary
  • Publications
  • Machine learning
• Five ways artificial intelligence is poised to revolutionize cancer care
  • Flatiron events
  • Point of care
  • Event recap
  • Machine learning
  • Artificial intelligence
• Using large language models to extract PD-L1 testing details from electronic health records

  Poster presented at: ISPOR US 2024; May 5-8, 2024; Atlanta, GA

  • Real-world evidence
  • Publication summary
  • Publications
  • Machine learning