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  1. NLST Data Requests
  2. NDR-176

NLST-579 Request for CT Images

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      https://cdas.cancer.gov/approved-projects/2359/

      Principal Investigator

      Name
      Seungwook Yang
      Degrees
      Ph.D
      Institution
      Samsung Electronics
      Position Title
      Research Scientist
      Email
      sw1315.yang@samsung.com

      About this Project

      Study
      NLST (Learn more about this study)
      Project ID
      NLST-579
      Title
      Exploration of deep learning-based model's lung cancer screening capabilities.
      Summary
      Although chest radiography has proven inferiority in terms of screening accuracy compared to computed tomography, augmenting human readers with deep learning-based computer-aided detection (CAD) model for pulmonary nodules may provide added benefits in screening. This project will first utilize radiographs from the NLST study as a standardized external validation set and compare the detection accuracies between a deep learning-based model and human readers, then the investigators will develop a new lung cancer prediction model involving the detection results.
      Aims

      • Exploration / validation of deep learning-based nodule detection system and comparison with human readers.
      • Development of a novel lung cancer prediction model incorporating deep learning-based nodule detection system's results.
        Collaborators
        Clinical Research Group, Health & Medical Equipment Business, Samsung Electronics

            tracyn T Nolan
            tracyn T Nolan
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